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2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	How many people were infected during the 1918 Spanish Influenza epidemic?	1,058	An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses	985
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What was the case fatality rate in the 1918 Spanish Influenza epidemic?	1,059	Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics	1,198
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What was the death toll in the 1918-1919 Spanish Influenza epidemic?	1,060	Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion	1,284
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Are the modern day Influenza viruses related to the 1918 Spanish Influenza virus?	1,062	All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses.	1,439
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Why is the Spanish Influenza virus the Mother of the modern influenza viruses?	1,063	The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics.	1,729
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	When was it determined that the 1918 pandemic was caused by the H1N1 Influenza virus?	1,064	That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic	2,355
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Did the Spanish Influenza or Swine flu or the H1N1 virus disappear in humans for some time?	1,065	descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs.	2,670
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	When did the Swine Flu (Spanish Influenza) virus reappear in humans?	1,066	But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically.	3,115
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What descendant lineages of the swine flu (Spanish Influenza) virus were identified in 2006?	1,068	2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage.	3,271
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Are the modern descendant influenza viruses as dangerous as the 1918 parent swine flu (Spanish Influenza) H1N1 virus?	1,070	None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus.	3,605
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	How dangerous are the modern H1N1 (swine flu) and the H3N2 (Influenza A) viruses compared to the 1918 H1N1 (swine flu Spanish Influenza) viruses?	1,072	the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present).	3,781
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Are the descendant H1N1 strains of the 1918 H1N1 swine flu (Spanish Influenza) virus, still prevalent?	1,073	H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction.	4,045
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Is the origin and epidemiology of the 1918 swine flu (Spanish Influenza) known?	1,075	ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic.	5,741
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What is the geographical origin of the H1N1 swine flu ?	1,082	Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context	6,409
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Is the geographical origin of the 1918 H1N1 swine flu known?	1,087	Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918)	6,125
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What is an unique feature of the 1918 swine flu?	1,088	the simultaneous (or nearly simultaneous) infection of humans and swin	7,949
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What season or time of the year do the new strains of influenza emerge?	1,089	Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years,	9,120
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Once appeared, when do the influenza like diseases occur in subsequent years?	1,090	confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants.	9,458
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	When did the first wave of the H1N1 swine flu (Spanish Influenza) occur?	1,091	a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months	9,822
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What was the death rate in the first wave of the 1918 swine flu pandemic?	1,092	Illness rates were high, but death rates in most locales were not appreciably above normal.	9,972
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	When were the second and the third wave of the 1918-1919 swine flu pandemic?	1,093	A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919	10,064
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What was the primary difference between the first wave and the 2nd and 3rd wave of the 1918-1919 swine flu pandemic?	1,094	the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves.	10,785
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Why the human influenza viruses do not disappear after herd immunity is developed?	1,096	The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant	11,043
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What are the circumstances that promote the spread of influenza virus?	1,099	lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow	11,707
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Do seasonal temperatures and humidity explain the appearance of the three waves of the 1918 swine flu?	1,101	such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November.	11,957
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Which virus samples from the 1918 swine flu pandemic have been identified?	1,105	pandemic Virus samples we have yet identiﬁed are from second-wave patients	14,082
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Are viruses in the first and third waves of the 1918 swine flu pandemic same or derived from the virus from the second wave of the swine flu?	1,106	nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it	14,163
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Was the 1918 swine flu virus novel to humans are was it derived from older viruses?	1,107	Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes	14,934
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Do avian flu viruses change over long periods?	1,108	Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods	15,425
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What is the typical age profile of mortality in Influenza diseases?	1,109	The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between	21,665
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What was the age profile of mortality in the 1918 swine flu?	1,110	age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age	21,925
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Which age group was most susceptible to die during the 1918 swine flu pandemic?	1,111	Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence	23,095
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What was the death rate among children during the 1918 swine flu pandemic?	1,112	those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups.	23,541
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	What theory provides partial explanation for the age-specific profile of the death rate in the 1918 swine flu pandemic?	1,113	the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era	24,099
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Is there a difference in the pathologic feature and course of disease between modern influenza pandemics and the 1918 swine flu pandemic?	1,114	the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today.	26,867
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Could the 1918 swine flu virus been controlled by modern day drugs or vaccines?	1,117	the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir.	27,291
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Why was there such a high death rate in the 19118 swine flu pandemic?	1,120	Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group	27,603
2,684	1918 Influenza: the Mother of All Pandemics Jeffery K. Taubenberger" and David M. Morens1- The “Spanish" influenza pandemic of 1918—1919, which caused :50 million deaths worldwide, remains an ominous warning to public health. Many questions about its origins, its unusual epidemiologic features, and the basis of its pathogenicity remain unanswered. The public health implications of the pandemic therefore remain in doubt even as we now grapple with the feared emergence of a pandemic caused by H5N1 or other virus. However, new information about the 1918 virus is emerging, for example, sequencing of the entire genome from archival autopsy tis- sues. But, the viral genome alone is unlikely to provide answers to some critical questions. Understanding the 1918 pandemic and its implications for future pandemics requires careful experimentation and in-depth historical analysis. ”Curiouser and curiouser/ ” criedAlice Lewis Carroll, Alice’s Adventures in Wonderland, 1865 An estimated one third of the world’s population (or z500 million persons) were infected and had clinical- ly apparent illnesses (1,2) during the 191871919 inﬂuenza pandemic. The disease was exceptionally severe. Case- fatality rates were >2.5%, compared to <0.1% in other inﬂuenza pandemics (3,4). Total deaths were estimated at z50 million (577) and were arguably as high as 100 mil- lion (7). The impact of this pandemic was not limited to 191871919. All inﬂuenza A pandemics since that time, and indeed almost all cases of inﬂuenza A worldwide (except- ing human infections from avian Viruses such as H5N1 and H7N7), have been caused by descendants of the 1918 Virus, including “drifted” H1N1 Viruses and reassorted H2N2 and H3N2 Viruses. The latter are composed of key genes from the 1918 Virus, updated by subsequently-incor— porated avian inﬂuenza genes that code for novel surface *Armed Forces Institute of Pathology, Rockville, Maryland, USA; and TNational Institutes of Health, Bethesda, Maryland, USA proteins, making the 1918 Virus indeed the “mother” of all pandemics. In 1918, the cause of human inﬂuenza and its links to avian and swine inﬂuenza were unknown. Despite clinical and epidemiologic similarities to inﬂuenza pandemics of 1889, 1847, and even earlier, many questioned whether such an explosively fatal disease could be inﬂuenza at all. That question did not begin to be resolved until the 1930s, when closely related inﬂuenza Viruses (now known to be H1N1 Viruses) were isolated, ﬁrst from pigs and shortly thereafter from humans. Seroepidemiologic studies soon linked both of these viruses to the 1918 pandemic (8). Subsequent research indicates that descendants of the 1918 Virus still persists enzootically in pigs. They probably also circulated continuously in humans, undergoing gradual antigenic drift and causing annual epidemics, until the 1950s. With the appearance of a new H2N2 pandemic strain in 1957 (“Asian ﬂu”), the direct H1N1 Viral descen- dants 0f the 1918 pandemic strain disappeared from human circulation entirely, although the related lineage persisted enzootically in pigs. But in 1977, human H1N1 Viruses suddenly “reemerged” from a laboratory freezer (9). They continue to circulate endemically and epidemically. Thus in 2006, 2 major descendant lineages of the 1918 H1N1 Virus, as well as 2 additional reassortant lineages, persist naturally: a human epidemic/endemic H1N1 line- age, a porcine enzootic H1N1 lineage (so-called classic swine ﬂu), and the reassorted human H3N2 Virus lineage, which like the human H1N1 Virus, has led to a porcine H3N2 lineage. None of these Viral descendants, however, approaches the pathogenicity of the 1918 parent Virus. Apparently, the porcine H1N1 and H3N2 lineages uncom- monly infect humans, and the human H1N1 and H3N2 lin- eages have both been associated with substantially lower rates ofillness and death than the virus of 1918. In fact, cur- rent H1N1 death rates are even lower than those for H3N2 lineage strains (prevalent from 1968 until the present). H1N1 Viruses descended from the 1918 strain, as well as H3N2 Viruses, have now been cocirculating worldwide for 29 years and show little evidence of imminent extinction. Trying To Understand What Happened By the early 1990s, 75 years of research had failed to answer a most basic question about the 1918 pandemic: why was it so fatal? No Virus from 1918 had been isolated, but all of its apparent descendants caused substantially milder human disease. Moreover, examination of mortality data from the 1920s suggests that within a few years after 1918, inﬂuenza epidemics had settled into a pattern of annual epidemicity associated with strain drifting and sub- stantially lowered death rates. Did some critical Viral genet- ic event produce a 1918 Virus of remarkable pathogenicity and then another critical genetic event occur soon after the 1918 pandemic to produce an attenuated H1N1 Virus? In 1995, a scientiﬁc team identiﬁed archival inﬂuenza autopsy materials collected in the autumn of 1918 and began the slow process of sequencing small Viral RNA fragments to determine the genomic structure of the causative inﬂuenza Virus (10). These efforts have now determined the complete genomic sequence of 1 Virus and partial sequences from 4 others. The primary data from the above studies (11717) and a number of reviews covering different aspects of the 1918 pandemic have recently been published ([8720) and conﬁrm that the 1918 Virus is the likely ancestor of all 4 of the human and swine H1N1 and H3N2 lineages, as well as the “extinct” H2N2 lineage. No known mutations correlated with high pathogenicity in other human or animal inﬂuenza Viruses have been found in the 1918 genome, but ongoing studies to map Virulence factors are yielding interesting results. The 1918 sequence data, however, leave unanswered questions about the ori- gin of the Virus (19) and about the epidemiology of the pandemic. When and Where Did the 1918 Inﬂuenza Pandemic Arise? Before and after 1918, most inﬂuenza pandemics developed in Asia and spread from there to the rest of the world. Confounding deﬁnite assignment of a geographic point of origin, the 1918 pandemic spread more or less simultaneously in 3 distinct waves during an z12-month period in 191871919, in Europe, Asia, and North America (the ﬁrst wave was best described in the United States in March 1918). Historical and epidemiologic data are inade- quate to identify the geographic origin of the Virus (21), and recent phylogenetic analysis of the 1918 Viral genome does not place the Virus in any geographic context ([9). Although in 1918 inﬂuenza was not a nationally reportable disease and diagnostic criteria for inﬂuenza and pneumonia were vague, death rates from inﬂuenza and pneumonia in the United States had risen sharply in 1915 and 1916 because of a major respiratory disease epidemic beginning in December 1915 (22). Death rates then dipped slightly in 1917. The ﬁrst pandemic inﬂuenza wave appeared in the spring of 1918, followed in rapid succes- sion by much more fatal second and third waves in the fall and winter of 191871919, respectively (Figure 1). Is it pos- sible that a poorly-adapted H1N1 Virus was already begin- ning to spread in 1915, causing some serious illnesses but not yet sufﬁciently ﬁt to initiate a pandemic? Data consis- tent with this possibility were reported at the time from European military camps (23), but a counter argument is that if a strain with a new hemagglutinin (HA) was caus- ing enough illness to affect the US national death rates from pneumonia and inﬂuenza, it should have caused a pandemic sooner, and when it eventually did, in 1918, many people should have been immune or at least partial- ly immunoprotected. “Herald” events in 1915, 1916, and possibly even in early 1918, if they occurred, would be dif- ﬁcult to identify. The 1918 inﬂuenza pandemic had another unique fea- ture, the simultaneous (or nearly simultaneous) infection of humans and swine. The Virus of the 1918 pandemic like- ly expressed an antigenically novel subtype to which most humans and swine were immunologically naive in 1918 (12,20). Recently published sequence and phylogenetic analyses suggest that the genes encoding the HA and neu- raminidase (NA) surface proteins of the 1918 Virus were derived from an avianlike inﬂuenza Virus shortly before the start of the pandemic and that the precursor Virus had not circulated widely in humans or swine in the few decades before (12,15, 24). More recent analyses of the other gene segments of the Virus also support this conclu- sion. Regression analyses of human and swine inﬂuenza sequences obtained from 1930 to the present place the ini- tial circulation of the 1918 precursor Virus in humans at approximately 191571918 (20). Thus, the precursor was probably not circulating widely in humans until shortly before 1918, nor did it appear to have jumped directly from any species of bird studied to date (19). In summary, its origin remains puzzling. Were the 3 Waves in 1918—1 919 Caused by the Same Virus? If So, How and Why? Historical records since the 16th century suggest that new inﬂuenza pandemics may appear at any time of year, not necessarily in the familiar annual winter patterns of interpandemic years, presumably because newly shifted inﬂuenza Viruses behave differently when they ﬁnd a uni- versal or highly susceptible human population. Thereafter, confronted by the selection pressures of population immu- nity, these pandemic Viruses begin to drift genetically and eventually settle into a pattern of annual epidemic recur- rences caused by the drifted Virus variants. Figure 1. Three pandemic waves: weekly combined inﬂuenza and pneumonia mortality, United Kingdom, 1918—1919 (21). In the 1918-1919 pandemic, a ﬁrst or spring wave began in March 1918 and spread unevenly through the United States, Europe, and possibly Asia over the next 6 months (Figure 1). Illness rates were high, but death rates in most locales were not appreciably above normal. A sec- ond or fall wave spread globally from September to November 1918 and was highly fatal. In many nations, a third wave occurred in early 1919 (21). Clinical similari- ties led contemporary observers to conclude initially that they were observing the same disease in the successive waves. The milder forms of illness in all 3 waves were identical and typical of inﬂuenza seen in the 1889 pandem- ic and in prior interpandemic years. In retrospect, even the rapid progressions from uncomplicated inﬂuenza infec- tions to fatal pneumonia, a hallmark of the 191871919 fall and winter waves, had been noted in the relatively few severe spring wave cases. The differences between the waves thus seemed to be primarily in the much higher fre- quency of complicated, severe, and fatal cases in the last 2 waves. But 3 extensive pandemic waves of inﬂuenza within 1 year, occurring in rapid succession, with only the briefest of quiescent intervals between them, was unprecedented. The occurrence, and to some extent the severity, of recur- rent annual outbreaks, are driven by Viral antigenic drift, with an antigenic variant Virus emerging to become domi- nant approximately every 2 to 3 years. Without such drift, circulating human inﬂuenza Viruses would presumably disappear once herd immunity had reached a critical threshold at which further Virus spread was sufﬁciently limited. The timing and spacing of inﬂuenza epidemics in interpandemic years have been subjects of speculation for decades. Factors believed to be responsible include partial herd immunity limiting Virus spread in all but the most favorable circumstances, which include lower environ- mental temperatures and human nasal temperatures (bene- ﬁcial to thermolabile Viruses such as inﬂuenza), optimal humidity, increased crowding indoors, and imperfect ven- tilation due to closed windows and suboptimal airﬂow. However, such factors cannot explain the 3 pandemic waves of 1918-1919, which occurred in the spring-sum- mer, summer—fall, and winter (of the Northern Hemisphere), respectively. The ﬁrst 2 waves occurred at a time of year normally unfavorable to inﬂuenza Virus spread. The second wave caused simultaneous outbreaks in the Northern and Southern Hemispheres from September to November. Furthermore, the interwave peri- ods were so brief as to be almost undetectable in some locales. Reconciling epidemiologically the steep drop in cases in the ﬁrst and second waves with the sharp rises in cases of the second and third waves is difﬁcult. Assuming even transient postinfection immunity, how could suscep- tible persons be too few to sustain transmission at 1 point, and yet enough to start a new explosive pandemic wave a few weeks later? Could the Virus have mutated profoundly and almost simultaneously around the world, in the short periods between the successive waves? Acquiring Viral drift sufﬁcient to produce new inﬂuenza strains capable of escaping population immunity is believed to take years of global circulation, not weeks of local circulation. And hav- ing occurred, such mutated Viruses normally take months to spread around the world. At the beginning of other “off season” inﬂuenza pan- demics, successive distinct waves within a year have not been reported. The 1889 pandemic, for example, began in the late spring of 1889 and took several months to spread throughout the world, peaking in northern Europe and the United States late in 1889 or early in 1890. The second recurrence peaked in late spring 1891 (more than a year after the ﬁrst pandemic appearance) and the third in early 1892 (21 ). As was true for the 1918 pandemic, the second 1891 recurrence produced of the most deaths. The 3 recur- rences in 1889-1892, however, were spread over >3 years, in contrast to 191871919, when the sequential waves seen in individual countries were typically compressed into z879 months. What gave the 1918 Virus the unprecedented ability to generate rapidly successive pandemic waves is unclear. Because the only 1918 pandemic Virus samples we have yet identiﬁed are from second-wave patients ([6), nothing can yet be said about whether the ﬁrst (spring) wave, or for that matter, the third wave, represented circulation of the same Virus or variants of it. Data from 1918 suggest that persons infected in the second wave may have been pro- tected from inﬂuenza in the third wave. But the few data bearing on protection during the second and third waves after infection in the ﬁrst wave are inconclusive and do lit- tle to resolve the question of whether the ﬁrst wave was caused by the same Virus or whether major genetic evolu- tionary events were occurring even as the pandemic exploded and progressed. Only inﬂuenza RNAipositive human samples from before 1918, and from all 3 waves, can answer this question. What Was the Animal Host Origin of the Pandemic Virus? Viral sequence data now suggest that the entire 1918 Virus was novel to humans in, or shortly before, 1918, and that it thus was not a reassortant Virus produced from old existing strains that acquired 1 or more new genes, such as those causing the 1957 and 1968 pandemics. On the con- trary, the 1918 Virus appears to be an avianlike inﬂuenza Virus derived in toto from an unknown source (17,19), as its 8 genome segments are substantially different from contemporary avian inﬂuenza genes. Inﬂuenza Virus gene sequences from a number ofﬁxed specimens ofwild birds collected circa 1918 show little difference from avian Viruses isolated today, indicating that avian Viruses likely undergo little antigenic change in their natural hosts even over long periods (24,25). For example, the 1918 nucleoprotein (NP) gene sequence is similar to that ofviruses found in wild birds at the amino acid level but very divergent at the nucleotide level, which suggests considerable evolutionary distance between the sources of the 1918 NP and of currently sequenced NP genes in wild bird strains (13,19). One way of looking at the evolutionary distance of genes is to com- pare ratios of synonymous to nonsynonymous nucleotide substitutions. A synonymous substitution represents a silent change, a nucleotide change in a codon that does not result in an amino acid replacement. A nonsynonymous substitution is a nucleotide change in a codon that results in an amino acid replacement. Generally, a Viral gene sub- jected to immunologic drift pressure or adapting to a new host exhibits a greater percentage of nonsynonymous mutations, while a Virus under little selective pressure accumulates mainly synonymous changes. Since little or no selection pressure is exerted on synonymous changes, they are thought to reﬂect evolutionary distance. Because the 1918 gene segments have more synony- mous changes from known sequences of wild bird strains than expected, they are unlikely to have emerged directly from an avian inﬂuenza Virus similar to those that have been sequenced so far. This is especially apparent when one examines the differences at 4-fold degenerate codons, the subset of synonymous changes in which, at the third codon position, any of the 4 possible nucleotides can be substituted without changing the resulting amino acid. At the same time, the 1918 sequences have too few amino acid diﬁerences from those of wild-bird strains to have spent many years adapting only in a human or swine intermedi- ate host. One possible explanation is that these unusual gene segments were acquired from a reservoir of inﬂuenza Virus that has not yet been identiﬁed or sampled. All of these ﬁndings beg the question: where did the 1918 Virus come from? In contrast to the genetic makeup of the 1918 pandem- ic Virus, the novel gene segments of the reassorted 1957 and 1968 pandemic Viruses all originated in Eurasian avian Viruses (26); both human Viruses arose by the same mech- anismireassortment of a Eurasian wild waterfowl strain with the previously circulating human H1N1 strain. Proving the hypothesis that the Virus responsible for the 1918 pandemic had a markedly different origin requires samples of human inﬂuenza strains circulating before 1918 and samples of inﬂuenza strains in the wild that more closely resemble the 1918 sequences. What Was the Biological Basis for 1918 Pandemic Virus Pathogenicity? Sequence analysis alone does not oﬁer clues to the pathogenicity of the 1918 Virus. A series of experiments are under way to model Virulence in Vitro and in animal models by using Viral constructs containing 1918 genes produced by reverse genetics. Inﬂuenza Virus infection requires binding of the HA protein to sialic acid receptors on host cell surface. The HA receptor-binding site conﬁguration is different for those inﬂuenza Viruses adapted to infect birds and those adapted to infect humans. Inﬂuenza Virus strains adapted to birds preferentially bind sialic acid receptors with 01 (273) linked sugars (27729). Human-adapted inﬂuenza Viruses are thought to preferentially bind receptors with 01 (2%) link- ages. The switch from this avian receptor conﬁguration requires of the Virus only 1 amino acid change (30), and the HAs of all 5 sequenced 1918 Viruses have this change, which suggests that it could be a critical step in human host adaptation. A second change that greatly augments Virus binding to the human receptor may also occur, but only 3 of5 1918 HA sequences have it (16). This means that at least 2 H1N1 receptor-binding vari- ants cocirculated in 1918: 1 with high—afﬁnity binding to the human receptor and 1 with mixed-afﬁnity binding to both avian and human receptors. No geographic or chrono- logic indication eXists to suggest that one of these variants was the precursor of the other, nor are there consistent dif- ferences between the case histories or histopathologic fea- tures of the 5 patients infected with them. Whether the Viruses were equally transmissible in 1918, whether they had identical patterns of replication in the respiratory tree, and whether one or both also circulated in the ﬁrst and third pandemic waves, are unknown. In a series of in Vivo experiments, recombinant inﬂuen- za Viruses containing between 1 and 5 gene segments of the 1918 Virus have been produced. Those constructs bearing the 1918 HA and NA are all highly pathogenic in mice (31). Furthermore, expression microarray analysis performed on whole lung tissue of mice infected with the 1918 HA/NA recombinant showed increased upregulation of genes involved in apoptosis, tissue injury, and oxidative damage (32). These ﬁndings are unexpected because the Viruses with the 1918 genes had not been adapted to mice; control experiments in which mice were infected with modern human Viruses showed little disease and limited Viral replication. The lungs of animals infected with the 1918 HA/NA construct showed bronchial and alveolar epithelial necrosis and a marked inﬂammatory inﬁltrate, which suggests that the 1918 HA (and possibly the NA) contain Virulence factors for mice. The Viral genotypic basis of this pathogenicity is not yet mapped. Whether pathogenicity in mice effectively models pathogenicity in humans is unclear. The potential role of the other 1918 pro- teins, singularly and in combination, is also unknown. Experiments to map further the genetic basis of Virulence of the 1918 Virus in various animal models are planned. These experiments may help deﬁne the Viral component to the unusual pathogenicity of the 1918 Virus but cannot address whether speciﬁc host factors in 1918 accounted for unique inﬂuenza mortality patterns. Why Did the 1918 Virus Kill So Many Healthy Young Ad ults? The curve of inﬂuenza deaths by age at death has histor- ically, for at least 150 years, been U-shaped (Figure 2), exhibiting mortality peaks in the very young and the very old, with a comparatively low frequency of deaths at all ages in between. In contrast, age-speciﬁc death rates in the 1918 pandemic exhibited a distinct pattern that has not been documented before or since: a “W—shaped” curve, similar to the familiar U-shaped curve but with the addition of a third (middle) distinct peak of deaths in young adults z20410 years of age. Inﬂuenza and pneumonia death rates for those 1534 years of age in 191871919, for example, were 20 times higher than in previous years (35). Overall, near- ly half of the inﬂuenza—related deaths in the 1918 pandem- ic were in young adults 20410 years of age, a phenomenon unique to that pandemic year. The 1918 pandemic is also unique among inﬂuenza pandemics in that absolute risk of inﬂuenza death was higher in those <65 years of age than in those >65; persons <65 years of age accounted for >99% of all excess inﬂuenza—related deaths in 191871919. In com- parison, the <65-year age group accounted for 36% of all excess inﬂuenza—related deaths in the 1957 H2N2 pandem- ic and 48% in the 1968 H3N2 pandemic (33). A sharper perspective emerges when 1918 age-speciﬁc inﬂuenza morbidity rates (21) are used to adj ust the W- shaped mortality curve (Figure 3, panels, A, B, and C [35,37]). Persons 65 years of age in 1918 had a dispro- portionately high inﬂuenza incidence (Figure 3, panel A). But even after adjusting age-speciﬁc deaths by age-specif— ic clinical attack rates (Figure 3, panel B), a W—shaped curve with a case-fatality peak in young adults remains and is signiﬁcantly different from U-shaped age-speciﬁc case- fatality curves typically seen in other inﬂuenza years, e.g., 192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14 years of age accounted for a disproportionate number of inﬂuenza cases, but had a much lower death rate from inﬂuenza and pneumonia than other age groups. To explain this pattern, we must look beyond properties of the Virus to host and environmental factors, possibly including immunopathology (e.g., antibody-dependent infection enhancement associated with prior Virus exposures [38]) and exposure to risk cofactors such as coinfecting agents, medications, and environmental agents. One theory that may partially explain these ﬁndings is that the 1918 Virus had an intrinsically high Virulence, tem- pered only in those patients who had been born before 1889, e.g., because of exposure to a then-circulating Virus capable of providing partial immunoprotection against the 1918 Virus strain only in persons old enough (>35 years) to have been infected during that prior era (35). But this the- ory would present an additional paradox: an obscure pre- cursor Virus that left no detectable trace today would have had to have appeared and disappeared before 1889 and then reappeared more than 3 decades later. Epidemiologic data on rates of clinical inﬂuenza by age, collected between 1900 and 1918, provide good evi- dence for the emergence of an antigenically novel inﬂuen- za Virus in 1918 (21). Jordan showed that from 1900 to 1917, the 5- to 15-year age group accounted for 11% of total inﬂuenza cases, while the >65-year age group accounted for 6 % of inﬂuenza cases. But in 1918, cases in Figure 2. “U-” and “W—” shaped combined inﬂuenza and pneumo- nia mortality, by age at death, per 100,000 persons in each age group, United States, 1911—1918. Influenza- and pneumonia- speciﬁc death rates are plotted for the interpandemic years 1911—1917 (dashed line) and for the pandemic year 1918 (solid line) (33,34). Incidence male per 1 .nao persunslage group Mortality per 1.000 persunslige group + Case—fataiity rale 1918—1919 Case fatalily par 100 persons ill wilh P&I pel age group Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific incidence rates per 1,000 persons per age group (panel A), death rates per 1,000 persons, ill and well combined (panel B), and case-fatality rates (panel C, solid line), US Public Health Service house-to-house surveys, 8 states, 1918 (36). A more typical curve of age-specific influenza case-fatality (panel C, dotted line) is taken from US Public Health Service surveys during 1928—1929 (37). the 5 to 15-year-old group jumped to 25% of inﬂuenza cases (compatible with exposure to an antigenically novel Virus strain), while the >65-year age group only accounted for 0.6% of the inﬂuenza cases, ﬁndings consistent with previously acquired protective immunity caused by an identical or closely related Viral protein to which older per- sons had once been exposed. Mortality data are in accord. In 1918, persons >75 years had lower inﬂuenza and pneumonia case-fatality rates than they had during the prepandemic period of 191171917. At the other end of the age spectrum (Figure 2), a high proportion of deaths in infancy and early childhood in 1918 mimics the age pat- tern, if not the mortality rate, of other inﬂuenza pandemics. Could a 1918-like Pandemic Appear Again? If So, What Could We Do About It? In its disease course and pathologic features, the 1918 pandemic was different in degree, but not in kind, from previous and subsequent pandemics. Despite the extraordi- nary number of global deaths, most inﬂuenza cases in 1918 (>95% in most locales in industrialized nations) were mild and essentially indistinguishable from inﬂuenza cases today. Furthermore, laboratory experiments with recombi- nant inﬂuenza Viruses containing genes from the 1918 Virus suggest that the 1918 and 1918-like Viruses would be as sensitive as other typical Virus strains to the Food and Drug Administrationiapproved antiinﬂuenza drugs riman- tadine and oseltamivir. However, some characteristics of the 1918 pandemic appear unique: most notably, death rates were 5 7 20 times higher than expected. Clinically and pathologically, these high death rates appear to be the result of several factors, including a higher proportion of severe and complicated infections of the respiratory tract, rather than involvement of organ systems outside the normal range of the inﬂuenza Virus. Also, the deaths were concentrated in an unusually young age group. Finally, in 1918, 3 separate recurrences of inﬂuenza followed each other with unusual rapidity, resulting in 3 explosive pandemic waves within a year’s time (Figure 1). Each of these unique characteristics may reﬂect genetic features of the 1918 Virus, but understand- ing them will also require examination of host and envi- ronmental factors. Until we can ascertain which of these factors gave rise to the mortality patterns observed and learn more about the formation of the pandemic, predictions are only educated guesses. We can only conclude that since it happened once, analogous conditions could lead to an equally devastating pandemic. Like the 1918 Virus, H5N1 is an avian Virus (39), though a distantly related one. The evolutionary path that led to pandemic emergence in 1918 is entirely unknown, but it appears to be different in many respects from the cur- rent situation with H5N1. There are no historical data, either in 1918 or in any other pandemic, for establishing that a pandemic “precursor” Virus caused a highly patho- genic outbreak in domestic poultry, and no highly patho- genic avian inﬂuenza (HPAI) Virus, including H5N1 and a number of others, has ever been known to cause a major human epidemic, let alone a pandemic. While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus. The 1918 Virus acquired this trait, but we do not know how, and we cur- rently have no way of knowing whether H5N1 Viruses are now in a parallel process of acquiring human-to-human transmissibility. Despite an explosion of data on the 1918 Virus during the past decade, we are not much closer to understanding pandemic emergence in 2006 than we were in understanding the risk of H1N1 “swine ﬂu” emergence in 1976. Even with modern antiviral and antibacterial drugs, vaccines, and prevention knowledge, the return of a pan- demic Virus equivalent in pathogenicity to the Virus of 1918 would likely kill >100 million people worldwide. A pandemic Virus with the (alleged) pathogenic potential of some recent H5N1 outbreaks could cause substantially more deaths. Whether because of Viral, host or environmental fac- tors, the 1918 Virus causing the ﬁrst or ‘spring’ wave was not associated with the exceptional pathogenicity of the second (fall) and third (winter) waves. Identiﬁcation of an inﬂuenza RNA-positive case from the ﬁrst wave could point to a genetic basis for Virulence by allowing differ- ences in Viral sequences to be highlighted. Identiﬁcation of pre-1918 human inﬂuenza RNA samples would help us understand the timing of emergence of the 1918 Virus. Surveillance and genomic sequencing of large numbers of animal inﬂuenza Viruses will help us understand the genet- ic basis of host adaptation and the extent of the natural reservoir of inﬂuenza Viruses. Understanding inﬂuenza pandemics in general requires understanding the 1918 pan- demic in all its historical, epidemiologic, and biologic aspects. Dr Taubenberger is chair of the Department of Molecular Pathology at the Armed Forces Institute of Pathology, Rockville, Maryland. His research interests include the molecular patho- physiology and evolution of inﬂuenza Viruses. Dr Morens is an epidemiologist with a long-standing inter- est in emerging infectious diseases, Virology, tropical medicine, and medical history. Since 1999, he has worked at the National Institute of Allergy and Infectious Diseases. References 1. Frost WH. Statistics of inﬂuenza morbidity. Public Health Rep. 19203558497. 2. Bumet F, Clark E. Inﬂuenza: a survey ofthe last 50 years in the light of modern work on the Virus of epidemic inﬂuenza. Melbourne: MacMillan; 1942. 3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976. 4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and public health. New York: Appleton-Century-Crofts; 1980. 5. Crosby A. America’s forgotten pandemic. Cambridge (UK): Cambridge University Press;1989. 6. Patterson KD, Pyle GF. The geography and mortality of the 1918 influenza pandemic. Bull Hist Med. 1991;65:4–21. 7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med 2002;76:105–15. 8. Shope RE. The incidence of neutralizing antibodies for swine influenza virus in the sera of human beings of different ages. J Exp Med. 1936;63:669–84. 9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity of influenza A (H1N1) viruses from epidemics in 1977–1978 to “Scandinavian” strains isolated in epidemics of 1950–1951. Virology. 1978;89:632–6. 10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG. Initial genetic characterization of the 1918 “Spanish” influenza virus. Science. 1997;275:1793–6. 11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses bearing the 1918 NS genes. Proc Natl Acad Sci U S A 2001;98:2746–51. 12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene. Proc Natl Acad Sci U S A 1999;96:1651–6. 13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and Taubenberger JK. Novel origin of the 1918 pandemic influenza virus nucleoprotein gene segment. J Virol. 2004;78:12462–70. 14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus matrix gene segment. J Virol. 2002;76:10717–23. 15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK. Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90. 16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis. 2003;9:1249–53. 17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning TG. Characterization of the 1918 influenza virus polymerase genes. Nature. 2005;437:889–93. 18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101. 19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the genetic origins of the 1918 pandemic influenza virus. Nat Rev Microbiol. 2004;2:909–14. 20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a killer comes into view. Virology. 2000;274:241–5. 21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical Association, 1927. 22. Capps J, Moody A. The recent epidemic of grip. JAMA. 1916;67:1349–50. 33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP. World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4. 24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J, Taubenberger JK. 1917 avian influenza virus sequences suggest that the 1918 pandemic virus did not acquire its hemagglutinin directly from birds. J Virol. 2002;76:7860–2. 25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J, Taubenberger JK. Relationship of pre-1918 avian influenza HA and NP sequences to subsequent avian influenza strains. Avian Dis. 2003;47:921–5. 26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al. Evolution of the H3 influenza virus hemagglutinin from human and nonhuman hosts. J Virol. 1992;66:1129–38. 27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC. Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature. 1988;333:426–31. 28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK, Robertson JS, et al. Specification of receptor-binding phenotypes of influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50. 29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova SS, Lvov DK, et al. Avian influenza A viruses differ from human viruses by recognition of sialyloigosaccharides and gangliosides and by a higher conservation of the HA receptor-binding site. Virology. 1997;233:224–34. 30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey TM, et al. A single amino acid substitution in the 1918 influenza virus hemagglutinin changes the receptor binding specificity. J Virol. 2005;79:11533–6. 31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7. 32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol. 2004;78:9499–511. 33. Grove RD, Hetzel AM. Vital statistics rates in the United States: 1940–1960. Washington: US Government Printing Office, 1968. 34. Linder FE, Grove RD. Vital statistics rates in the United States: 1900–1940. Washington: US Government Printing Office, 1943. 35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, Fukuda K. Pandemic versus epidemic influenza mortality: a pattern of changing age distribution. J Infect Dis 1998;178:53–60. 36. Frost WH. The epidemiology of influenza. Public Health Rep. 1919;34:1823–61. 37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative data for the epidemic of 1918–1919. Public Health Rep. 1931;46:1909–37. 38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514. 39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al. Re-emergence of fatal human influenza A subtype H5N1 disease. Lancet. 2004;363:617–9. Address for correspondence: Jeffery K. Taubenberger, Department of Molecular Pathology, Armed Forces Institute of Pathology, 1413 Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA; fax. 301-295-9507; email: [email protected] The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the Centers for Disease Control and Prevention or the institutions with which the authors are affiliated.	Is the molecular basis of human adaptation of a virus understood?	1,123	While data bearing on inﬂuenza Virus human cell adaptation (e.g., receptor binding) are beginning to be understood at the molecular level, the basis for Viral adaptation to efﬁcient human-to- human spread, the chief prerequisite for pandemic emer- gence, is unknown for any inﬂuenza Virus.	29,201
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	What was the initial growth phase pattern?	1,872	exponential growth pattern	1,435
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	What was the result of under-reporting?	1,875	469 (95% CI: 403−540) unreported cases from 1 to 15 Januar	1,514
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	What is R0?	1,877	basic reproduction number,	836
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	What is likely increase of the reporting rate after the 17th January 2020?	1,879	reased 21-fold (95% CI: 18	1,649
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	What is the estimated value of R0?	1,880	019-nCoV at 2.56 (95% CI	1,779
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	What is the likely period of under-reporting?	1,881	to have occurred during the first ha	1,865
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	Where and when was 2019-nCOV first identified?	1,882	s first identified in Wuhan, China	2,064
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	What are some of the symptoms caused by the virus?	1,884	ymptoms including fever, cough, and sh	2,151
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	What was the cumulative number of reported cases by 1 January 2020?	1,886	sed	2,266
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	As of 26 January 2020, what had the outbreak resulted in?	1,889	k had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in	2,405
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	As of 26 January 2020, what countries had sporadic cases?	1,891	were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and	2,574
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	What was the result of the Imperial College estimation?	1,892	at there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95	2,927
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	Who release the time series data from 10th to 20th January 2020?	1,893	y released by the Wuhan Municipal	3,981
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	Who released the time series data from after 21st January 2020?	1,894	, and later by the National Health C	4,064
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	How was the epidemic curve modelled?	1,895	, the C i series, as an exponential growi	5,150
2,620	Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak https://doi.org/10.3390/jcm9020388 SHA: bf20dda99538a594eafc258553634fd9195104cb Authors: Zhao, Shi; Musa, Salihu S.; Lin, Qianying; Ran, Jinjun; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Yang, Lin; Gao, Daozhou; He, Daihai; Wang, Maggie H. Date: 2020 DOI: 10.3390/jcm9020388 License: cc-by Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403−540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18−25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49−2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation. Text: A novel coronavirus (2019-nCoV) infected pneumonia infection, which is deadly [1] , was first identified in Wuhan, China in December 2019 [2] . The virus causes a range of symptoms including fever, cough, and shortness of breath [3] . The cumulative number of reported cases slowly increased to cumulative 41 cases by 1 January 2020, and rapidly increased after 16 January 2020. As of 26 January 2020, the still ongoing outbreak had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in mainland China [4] , and sporadic cases exported from Wuhan were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and the United States, please see the World Health Organization (WHO) news release via https://www.who.int/csr/don/en/ from 14 to 21 January 2020. Using the number of cases exported from Wuhan to other countries, a research group at Imperial College London estimated that there had been 4000 (95%CI: 1000-9700) cases in Wuhan with symptoms onset by 18 January 2020, and the basic reproduction number (R 0 ) was estimated at 2.6 (95%CI: 1.5-3.5) [5] . Leung et al. drew a similar conclusion and estimated the number of cases exported from Wuhan to other major cities in China [6] , and the potentials of travel related risks of disease spreading was also indicated by [7] . Due to an unknown reason, the cumulative number of cases remained at 41 from 1 to 15 January 2020 according to the official report, i.e., no new case was reported during these 15 days, which appears inconsistent with the following rapid growth of the epidemic curve since 16 January 2020. We suspect that the 2019-nCoV cases were under-reported roughly from 1 to 15 January 2020. In this study, we estimated the number of unreported cases and the basic reproduction number, R 0 , of 2019-nCoV in Wuhan from 1 to 15 January 2020 based on the limited data in the early outbreak. The time series data of 2019-nCoV cases in mainland China were initially released by the Wuhan Municipal Health Commission from 10 to 20 January 2020 [8] , and later by the National Health Commission of China after 21 January 2020 [9] . The case time series data in December 2019 were obtained from a published study [3] . All cases were laboratory confirmed following the case definition by the national health commission of China [10] . We chose the data up to 24 January 2020 instead of to the present study completion date. Given the lag between timings of case confirmation and news release of new cases, the data of the most recent few days were most likely to be tentative, and thus they were excluded from the analysis to be consistent. We suspected that there was a number of cases, denoted by ξ, under-reported from 1 to 15 January 2020. The cumulative total number of cases, denoted by C i , of the i-th day since 1 December 2019 is the summation of the cumulative reported, c i , and cumulative unreported cases, Ξ i . We have C i = c i + Ξ i , where c i is observed from the data, and Ξ i is 0 for i before 1 January and ξ for i after 15 January 2020. Following previous studies [11, 12] , we modelled the epidemic curve, i.e., the C i series, as an exponential growing Poisson process. Since the data from 1 to 15 January 2020 appeared constant due to unclear reason(s), we removed these data from the fitting of exponential growth. The ξ and the intrinsic growth rate (γ) of the exponential growth were to be estimated based on the log-likelihood, denoted by , from the Poisson priors. The 95% confidence interval (95% CI) of ξ was estimated by the profile likelihood estimation framework with cutoff threshold determined by a Chi-square quantile [13] , χ 2 pr = 0.95, df = 1 . With γ estimated, the basic reproduction number could be obtained by R 0 = 1/M(−γ) with 100% susceptibility for 2019-nCoV presumed at this early stage. Here, the function M(·) was the Laplace transform, i.e., the moment generating function, of the probability distribution for the serial interval (SI) of the disease [11, 14] , denoted by h(k) and k is the mean SI. Since the transmission chain of 2019-nCoV remained unclear, we adopted the SI information from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which share the similar pathogen as 2019-nCoV [15] [16] [17] . We modelled h(k) as Gamma distributions with mean of 8.0 days and standard deviation (SD) of 3.6 days by averaging the SI mean and SD of SARS, mean of 7.6 days and SD of 3.4 days [18] , and MERS, mean of 8.4 days and SD of 3.8 days [19] . We were also interested in inferring the patterns of the daily number of cases, denoted by ε i for the i-th day, and thus it is obviously that C i = C i−1 + ε i . A simulation framework was developed for the iterative Poisson process such that E[ denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403-540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R 0 was estimated at 2.56 (95% CI: 2.49-2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R 0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (C i ) remarkably well, see Figure 1c iterative Poisson process such that denoted the expectation. The simulation was implemented starting from 1 January 2020 with a cumulative number of cases seed of 40, the same as reported on 31 December 2019. We conducted 1000 samples and calculated the median and 95% CI. The number of 2019-nCoV unreported cases was estimated at 469 (95% CI: 403−540), see Figure 1a , which was significantly larger than 0. This finding implied the occurrence of under-reporting between 1 and 15 January 2020. After accounting for the effect of under-reporting, the R0 was estimated at 2.56 (95% CI: 2.49−2.63), see Figure 1b , which is consistent with many existing online preprints with range from 2 to 4 [5, [20] [21] [22] . With the R0 of 2.56 and ξ of 469, the exponential growing framework fitted the cumulative total number of cases (Ci) remarkably well, see Figure 1c , referring to McFadden's pseudo-R-squared of 0.99. show the exponential growth fitting results of the cumulative number of cases (Ci) and the daily number of cases (εi) respectively. In panels (c) and (d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an panels (a,b) , the green shading area represents the 95% CI (on the horizontal axis), and the vertical green line represents the maximum likelihood estimate (MLE) of the number of unreported cases. With the MLE of R 0 at 2.56, panels (c,d) show the exponential growth fitting results of the cumulative number of cases (C i ) and the daily number of cases (ε i ) respectively. In panels (c,d), the gold squares are the reported cases, the blue bold curve represents the median of the fitting results, the dashed blue curves are the 95% CI of the fitting results, and the purple shading area represents the time window from 1 to 15 January 2020. In panel (c), the blue dots are the cumulative total, i.e., reported and unreported, number of cases. In panel (d), the grey curves are the 1000 simulation samples. Our estimation of R 0 rely on the SI of 2019-nCoV, which remains unknown as of 26 January 2020. In this work, we employed the SIs of SARS and MERS as approximations to that of 2019-nCoV. The determination of SI requires the knowledge of the chain of disease transmission that needs a sufficient number of patient samples and periods of time for follow-up [23] , and thus this is unlikely to be achieved shortly. However, using SIs of SARS and MERS as approximation could provide an insight into the transmission potential of 2019-nCoV at the early outbreak. We note that slightly varying the mean and SD of SI would not affect our main conclusions. The R 0 of 2019-nCoV was estimated at 2.56 (95% CI: 2.49-2.63), and it is generally in line with those of SARS, i.e., 2-5 [19, 24, 25] , and MERS, i.e., 2.7-3.9 [26] . For the simulated daily number of cases (ε i ), see Figure 1d , we found that ε i matched the observed daily number after 17 January 2020, but was significantly larger than the observations from 1 to 17 January 2020. This finding implied that under-reporting was likely to have occurred in the first half of January 2020. We estimated that the reporting rate after 17 January 2020 increased 21-fold (95% CI: [18] [19] [20] [21] [22] [23] [24] [25] compared to the situation from 1 to 17 January 2020 on average. One of the possible reasons was that the official diagnostic protocol was released by WHO on 17 January 2020 [27] , and the diagnosis and reporting efforts of 2019-nCoV infections probably increased. Thereafter, the daily number of newly reported cases started increasing rapidly after 17 January 2020, see Figure 1d . We conducted additional sensitivity analysis by varying the starting date of the under-reporting time window, e.g., 1 January 2020 in the main results, from 2 December 2019 to 3 January 2020, and we report our estimates largely hold. The exact value of the reporting rate was difficult to determine due to lack of serological surveillance data. The reporting rate can be determined if serological surveillance data are available for a population; we would know who was infected (seropositive) and who was not (seronegative), with high confidence. The reporting rate is the ratio of reported cases over the number of seropositive individuals. It was statistically evident that increasing in reporting was likely, and thus it should be considered in the future investigation of this outbreak. Previous preprint suggested cumulative cases of 1723 (95% CI: 427-4471) as of 12 January 2020, and 4000 (95% CI: 1000-9700) as of 18 January 2020 based on the aggregated international export cases [5] . Our analysis yielded cumulative cases of 280 (95% CI: 128-613) as of 12 January 2020, and 609 (95% CI: 278-1333) as of 18 January 2020 based on the exponential growing mechanistic in the early outbreak. Although our estimate case number appeared to have a lower mean than those estimated by Imai et al. [5] , they are not statistically different. This study applied a different screening effort to detect the 2019-nCoV cases from that in Imai et al. [5] . Imai et al. assumed the average screening effort at overseas airports that covered travelers arriving from Wuhan. Whereas we assumed a constant screening effort applied in Wuhan at the same point of time, and then a number of cases (i.e., ξ) should have been reported yet failed to be reported in the first half of January 2020 due to all sorts of reasons. It is not surprising that different assumptions yielded different results, and this difference in screening effort also partly explained why the detected cases out of China mainly presented mild symptoms. Thus, it was reasonable that our estimates appeared lower than those estimated by Imai et al. [5] . It must be emphasized that such a gap in the knowledge would be resolved by serological survey study (for a large population to approximate the actual positive rate) or an explicit estimation of the actual reporting rate. Under-reporting was likely to have occurred and resulted in 469 (95% CI: 403-540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18-25) compared with the situation from 1 to 17 January 2020 on average, and it should be considered in future investigation. We estimated the R 0 at 2019-nCoV to be 2.56 (95% CI: 2.49-2.63). Author Contributions: All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript. All authors have read and agreed to the published version of the manuscript.	How was the epidemic curve modeled?	1,907	, the C i series, as an exponential growin	5,150
2,674	A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version) https://doi.org/10.1186/s40779-020-0233-6 SHA: fd28e6d03eef27b0454f13ca539dc1498242a4c2 Authors: Jin, Ying-Hui; Cai, Lin; Cheng, Zhen-Shun; Cheng, Hong; Deng, Tong; Fan, Yi-Pin; Fang, Cheng; Huang, Di; Huang, Lu-Qi; Huang, Qiao; Han, Yong; Hu, Bo; Hu, Fen; Li, Bing-Hui; Li, Yi-Rong; Liang, Ke; Lin, Li-Kai; Luo, Li-Sha; Ma, Jing; Ma, Lin-Lu; Peng, Zhi-Yong; Pan, Yun-Bao; Pan, Zhen-Yu; Ren, Xue-Qun; Sun, Hui-Min; Wang, Ying; Wang, Yun-Yun; Weng, Hong; Wei, Chao-Jie; Wu, Dong-Fang; Xia, Jian; Xiong, Yong; Xu, Hai-Bo; Yao, Xiao-Mei; Yuan, Yu-Feng; Ye, Tai-Sheng; Zhang, Xiao-Chun; Zhang, Ying-Wen; Zhang, Yin-Gao; Zhang, Hua-Min; Zhao, Yan; Zhao, Ming-Juan; Zi, Hao; Zeng, Xian-Tao; Wang, Yong-Yan; Wang, Xing-Huan; Management, for the Zhongnan Hospital of Wuhan University Novel Coronavirus; Research Team, Evidence-Based Medicine Chapter of China International Exchange; Promotive Association for, Medical; Health, Care Date: 2020 DOI: 10.1186/s40779-020-0233-6 License: cc-by Abstract: In December 2019, a new type viral pneumonia cases occurred in Wuhan, Hubei Province; and then named “2019 novel coronavirus (2019-nCoV)” by the World Health Organization (WHO) on 12 January 2020. For it is a never been experienced respiratory disease before and with infection ability widely and quickly, it attracted the world’s attention but without treatment and control manual. For the request from frontline clinicians and public health professionals of 2019-nCoV infected pneumonia management, an evidence-based guideline urgently needs to be developed. Therefore, we drafted this guideline according to the rapid advice guidelines methodology and general rules of WHO guideline development; we also added the first-hand management data of Zhongnan Hospital of Wuhan University. This guideline includes the guideline methodology, epidemiological characteristics, disease screening and population prevention, diagnosis, treatment and control (including traditional Chinese Medicine), nosocomial infection prevention and control, and disease nursing of the 2019-nCoV. Moreover, we also provide a whole process of a successful treatment case of the severe 2019-nCoV infected pneumonia and experience and lessons of hospital rescue for 2019-nCoV infections. This rapid advice guideline is suitable for the first frontline doctors and nurses, managers of hospitals and healthcare sections, community residents, public health persons, relevant researchers, and all person who are interested in the 2019-nCoV. Text: In December 2019, the 2019 novel coronavirus (2019-nCoV) was discovered and identified in the viral pneumonia cases that occurred in Wuhan, Hubei Province, China; And then was named by the World Health Organization (WHO) on 12 January 2020. In the following month, the 2019-nCoV quickly spreading inside and outside of Hubei Province and even other countries. What's more, the sharp increase of the case number caused widespread panic among the people. Medical professionals require an up-to-date guideline to follow when an urgent healthcare problem emerging. In response to the requests for reliable advice from frontline clinicians and public healthcare professionals managing 2019-nCoV pandemics, we developed this rapid advance guideline, involving disease epidemiology, etiology, diagnosis, treatment, nursing, and hospital infection control for clinicians, and also for public health workers and community residents. This guideline was prepared in accordance with the methodology and general rules of WHO Guideline Development and the WHO Rapid Advice Guidelines [1, 2] . This guideline development group is multidisciplinary and composed of individuals from health professionals and methodologists. Health professionals included frontline clinical doctors, nurses who work in departments of respiratory medicine, fever clinic, critical medicine, emergency, infectious disease, and experts of respiratory infectious disease and hospital management board. The methodologists included methodologists of guideline development, systematic review, and literature searching professionals. This guideline is suitable for frontline doctors and nurses, managers of hospitals and healthcare sections, healthy community residents, personnel in public healthcare, relevant researchers, and all persons who are interested in the 2019-nCoV management. This guideline is aimed to serve the healthcare professionals to tackle the suspected 2019-nCoV infected cases, confirmed 2019-nCoV infected cases, clustered 2019-nCoV infected cases, and those with close contacts or suspicious exposure to 2019-nCoV infected cases. Oral inquiry for financial interests of relevant personal was conducted at the first meeting while to start this guideline. Relevant financial as well as nonfinancial interests were surveyed and disclosed and subsequently assessed in consensus conference in order to minimize potential bias in guideline development. Finally, there is no conflict of interests for all the personnel participating to prepare this guideline. This guideline is a rapid guideline to responding to the emerging infectious disease of 2019-nCoV. Due to the urgent need and tight work schedule, we conducted no wide-range survey but a discussion meeting with front-line clinicians who managed patients with 2019-nCoV infections to finalize guideline topics and key questions. 2.6 Literature searching and preparation of evidence profiles 2.6.1 General notes Considering the lack of direct evidence for this newly identified 2019-nCoV infection, we searched and referred to the guidelines that related to the SARS (Severe Acute Respiratory Syndrome), MERS (Middle East Respiratory Syndrome), and influenza. We also referred to the guidelines which were newly-issued by the National Health Commission of People's Republic of China and WHO for 2019-nCoV. In addition, we have an independent literature searching team to search available indirect evidence from systematic reviews and/or RCTs (randomized controlled trials), which were for the treatment and/ or chemoprophylaxis of SARS, MERS, or other influenza virus infections. If the existing evidence addressed topics or questions covered by the guideline, then its quality should be assessed. If there is a lack of higher-level quality evidence, our panel considered observational studies and case series. Because of the limited time, we did not perform new systematic review. We identified relevant literature up to 20 January 2020. We searched the bibliographic databases: PubMed, Embase, and Cochrane library. We also searched following websites: the WHO (https://www.who.int/), CDC (Centers for Disease Control and Prevention, https://www.cdc.gov/), NICE (National Institute for Health and Clinical Excellence, https://www.nice.org.uk/), National Health Commission of the People's Republic of China (http://www.nhc.gov. cn/), and National Administration of Traditional Chinese Medicine (http://www.satcm.gov.cn/). As the 2019-nCoV is a newly identified pathogen responsible for the outbreak of the pandemic disease, there is no sufficient evidence to reveal the whole nature of this virus. In these situations, obtaining evidence from the experts who fighting the disease on the frontline can be efficient and the main source [3] . Until to 24:00 on 29 January 2020, 11,500 persons were screened, and 276 were identified as suspected infectious victims, and 170 were diagnosed (including 33 in critical condition) for 2019-nCoV infection in Zhongnan Hospital of Wuhan University. During this process, frontline clinicians and nurses have accumulated valuable experience in the diagnosis, treatment and nursing for 2019-nCoV infected patients. Hence, these experiences were assessed and then used as "Expert Evidence" for our guideline development. We took interviews and group surveys to collect information on treatment evidence during the guideline panel's meeting, so that it could be integrated into the guideline panel in the summary of findings (see Additional files 1 and 2). Experts' evidence can be solicited by the description of case reports, summaries, and reports of topics or questions of all cases they management. We accorded to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) basic approaches and rules [4, 5] , and particularly considered experts' evidence to assess the quality of a body of evidence to make recommendations. The quality of evidence reflects whether the extent to which our confidence estimating the effect is adequate to support a particular recommendation. The level of evidence was categorized as "high quality", "moderate quality", "low quality", or "very low quality"; Recommendations were classified as "strong" or "weak." The strong recommendation does not always mean there is sufficient intervention effectiveness. Besides the effectiveness of intervention, the forming of recommendations is based on the severity of the disease, patient willingness, safety, and economics [4] . See Tables 1 and 2 [4, 6] . Before meetings, experts' evidence was collected systematically and available to panel members. Once the evidence has been identified and assessed, recommendations were formulated based on the evidence by a face-to-face meeting of panel members and supplemented by experts participating in the panel meeting. Experts' evidence was highly valued in this guideline development. During the consensus process, if the evidence was agreed on by more than 70% frontline clinicians in the consensus meeting, it is considered as highquality evidence. In specific recomendations, we used "should" or "strongly recommend" for strong recommendations; whereas, "suggest" or "consider" was used for weak ones. This guideline was published in both Chinese and English versions at the same time. Due to space limitations, the current standard revision does not include evidence descriptions. The full revision will be published in New Medicine (Chinese name: Yixue Xinzhi; http://www. jnewmed.com/), Volume 30 and Issue 1 2020 [7] . Since December 2019, multiple cases occurring unexplainable pneumonia were successively reported in some hospitals in Wuhan city with a history of exposure to a large Hua'nan seafood market in Wuhan city, Hubei province, China. It has been confirmed to be an acute respiratory infection caused by a novel coronavirus. So far, the number of cases without a history of the Hua'nan seafood market exposure is increasing. In addition, clustered cases and confirmed cases without a history of travel to Wuhan emerged. Also, confirmed cases without clear exposure to the Wuhan seafood market have been found in many foreign countries or regions [8] . At 24:00 on 26 January 2020, the National Health Commission of the People's Republic of China has recorded a total of 2744 confirmed cases of pneumonia with 2019-nCoV infection from 30 provinces (districts and cities), including 461 severe cases and 80 deaths. A total of 51 cases have been cured and discharged. At present, 5794 suspected cases were recorded, 32,799 with close contacts to the confirmed patients have been tracked, 583 people were released from medical observation that day, and 30,453 people were still undergoing medical observation. A total of confirmed cases were reported from Hong Kong, Macao and Taiwan of China: 8 cases in Hong Kong, 5 cases in Macao, and 4 cases in Taiwan. In addition, confirmed cases had been reported from abroad: 7 in Thailand, 4 in Australia, 4 in Singapore, 3 in France, 3 in Japan, 3 in Korea, 3 in Wild animal, bats [10] is the most possible host of the 2019-nCoV. It requires further confirmation whether pneumonia infected by the 2019-nCoV is transmitted directly from bats or through an intermediate host. It is believed that clarifying the source of the virus will help determine zoonotic transmission patterns [11] . Up to present, the main infection source was the patients who with pneumonia infected by the 2019-nCoV. Respiratory droplet transmission is the main route of transmission, and it can also be transmitted through contact [12] . Although many details, such as the source of the virus and its ability to spread between people remain unknown, an increasing number of cases show the signs of human-tohuman transmission [8, 13] . The 2019-nCoV isolated from the lower respiratory tract of patients with unexplainable pneumonia in Wuhan, and it is a novel coronavirus belonging to the β genus. The 2019-nCoV has an envelope; its particles are round or oval, often polymorphic, with a diameter from 60 nm to 140 nm. Its genetic characteristics are significantly different from SARSr-CoV (SARS related coronaviruses) and MERSr-CoV (MERS related coronaviruses). Current research shows it has more than 85% homology with SARSr-CoV (bat-SL-CoVZC45). 2019-nCoV can be found in human respiratory epithelial cells 96 h after in vitro isolation and culture, while it takes about 6 days in VeroE6 or Huh-7 cell lines [12] . The source of the virus, the time span of the patients discharging infective virus, and the pathogenesis are still not clear [14] . No evidence of viral mutation has been found so far [14] . It is necessary to obtain much more clinically isolated viruses with time and geographical variety to assess the extent of the virus mutations, and also whether these mutations indicate adaptability to human hosts [11] . Based on currently epidemiological survey, the latency period is generally from 3 to 7 days, with a maximum of 14 days [10] . Unlike SARSr-CoV, 2019-nCoV is contagious during the latency period [15] . The evidence agreed on by more than 70% frontline clinicians in consensus meeting is viewed as high-quality evidence The population is generally susceptible to the virus. The elderly and those with underlying diseases show more serious conditions after infection, and children and infants also get infected by the 2019-nCoV. From current knowledge of the cases, most patients have a good prognosis, the symptoms of children are relatively mild, and a few patients are in critical condition. Death cases are more frequently seen in the elderly and those with chronic underlying diseases [12] . The newest study including the first 41 confirmed cases admitted to Wuhan between 16 December 2019 and 2 January 2020 showed the median age of patients was 49 years; and the main underlying diseases were diabetes, hypertension, and cardiovascular diseases. Of them, 12 cases experienced acute respiratory distress syndrome (ARDS), 13 cases were admitted to the intensive care unit (ICU), and 6 cases died [16] . Patients with any 2 of the following clinical features and any epidemiological risk: (1) clinical features: fever, imaging features of pneumonia, normal or reduced white blood cell count, or reduced lymphocyte count in the early stages of the disease onset. (2) epidemiologic risk: a history of travel to or residence in Wuhan city, China or other cities with continuous transmission of local cases in the last 14 days before symptom onset; contact with patients with fever or respiratory symptoms from Wuhan city, China or other cities with continuous transmission of local cases in the last 14 days before symptom onset; or epidemiologically connected to 2019-nCoV infections or clustered onsets [12] . Those with one of the following pathogenic evidence is the confirmed case: (1) positive for the 2019-nCoV by the real-time PCR test for nucleic acid in respiratory or blood samples [17] . 2) viral gene sequencing shows highly homogeneity to the known 2019-nCoV in respiratory or blood samples [12] . Suspected clustering cases are defined when one confirmed case and at the same time, one or more cases of fever or respiratory infection are found in a small area (such as a family, a construction site, a unit, etc.) within 14 days. Under the above circumstances, 2 or more confirmed cases are found, and there is the possibility of human-tohuman transmission due to close contact or infection due to co-exposure, then it is determined as a clustered case [8, 18] . Those who have one of the following contacts after the onset of confirmed cases in the absence of effective protection [18] : (1) those who live, study, work, or have close contact with the confirmed cases, or other close contacts such as working closely with or sharing the same classroom or living in the same house with the confirmed case. (2) medical and nursing staffs and their family members living with them, who treated, nursed or visited the confirmed case, or other personnel who have similar close contact with the case, such as providing direct treatment or care of the case, visiting the case or staying in a closed environment where the cases are located; other patients or caregivers in the same room with the case. (3) people who have close contact with the patients in a same transport vehicle, including those who had taken care of the patients on the vehicle; the person who had companied the patients (family members, colleagues, friends, etc.); other passengers and traffic staff considered having likely close contact with the patients by investigation and evaluation. (4) other circumstances considered to be closely contacted with the person with close contact with the patients by the professional investigation and evaluation. Persons with suspicious exposure are those who are exposed without effective protection to processing, sales, handling, distributing, or administrative management of wild animals, materials, and the environments that are positive for the 2019-nCoV test [18] . Persons with close contacts and suspicious exposure should be advised to have a 14-day health observation period, which starts from the last day of contact with the 2019-nCoV infected patients or suspicious environmental exposure. Once they display any symptoms, especially fever, respiratory symptoms such as coughing, shortness of breath, or diarrhea, they should reach out for medical attention immediately [19] . Contact surveillance should be carried out for those who had exposed to accidental contact, low-level exposure to suspected or confirmed patients, i.e. checking any potential symptoms when carrying out daily activities [20] . See Table 3 for details [21] . Patients with a suspected infection should be isolated, monitored, and diagnosed in hospital as soon as possible. Doctors should make recommendations based on the patient's situation. Patients with mild symptoms and suspected infection may consider in-home isolation and home care (weak recommendation). Suspected infected with severe symptoms and those who need to stay in hospital for observation by doctor's judgment should follow the isolation guidelines for suspected patients (see Tables 4 and 5 for details). It should also be noted that: (1) whether the suspected patients should be given in-home isolation and care or not requires careful clinical evaluation and safety assessment by professionals. (2) if the suspected patients do not get improvement in the symptoms or even worsened in condition during home care, they need to go to the doctor for treatment. (3) during the period of home care, the patients' medication and symptoms should be closely recorded and their caregivers should also monitor their body temperature daily. Throughout the period of home care, healthcare personnel should perform regular (e.g., daily) follow-up through face-to-face visits or phone interviews (ideally, if feasible) to follow the progress of symptoms and, if necessary, specific diagnostic tests should be conducted [14, 19, 21] . International visitors should take routine precautions when entering and leaving the affected areas, including avoiding close contacts with people with acute respiratory infection, washing hands frequently, especially after contacting with the sick or their surrounding environment; following appropriate coughing etiquette; and avoiding close contact with live or dead farming animals or bats or other wild animals [22, 23] . Passengers should avoid unnecessary travel as possible. If they had travelled to Hubei Province (especially Wuhan city) in the past 14 days and is in fever, cough or difficulty in breathing, they should: (1) see a doctor immediately; (2) call the doctor about his/her recent trips and symptoms before going to the doctor's office or emergency room; (3) avoid contact with others; (4) not to travel around; (5) cover mouth and nose with a tissue or sleeve (not hands) when coughing or sneezing; and (6) wash hands with soap and water for at least 20 s. If soap and water are not available, use alcohol-based hand sanitizers [24] . The 2019-nCoV infected cases have symptoms like fever, fatigue, dry cough, dyspnea etc., with or without nasal congestion, runny nose or other upper respiratory symptoms [13, 16] . Despite the atypical symptoms were reported [25] , Nan-Shan Zhong, the academician of Chinese Academy of Engineering in an exclusive interview with Xinhua News Agency on 28 January 2020, pointed out that fever is still the typical symptom of 2019-nCoV infection. Patients with mild symptoms may not present positive signs. Patients in severe condition may have shortness of breath, moist rales in lungs, weakened breath sounds, dullness in percussion, and increased or decreased tactile speech tremor, etc. The imaging findings vary with the patient's age, immunity status, disease stage at the time of scanning, underlying diseases, and drug interventions. When walking on the road or waiting in the hospital, try to stay away from other people (at least 1 m away) and wear a mask. The family members accompanying those for inspection should immediately follow the monitoring recommendations to close contacts, keep the respiratory hygiene and clean their hands properly. The community or street hospital should be informed before the suspected contacts to the hospital. The vehicle used should be cleaned and disinfected with 500 mg/L chlorine-containing disinfectant, and the window should be opened for ventilation. The imaging features of lesions show: (1) dominant distribution (mainly subpleural, along the bronchial vascular bundles); (2) quantity (often more than three or more lesions, occasional single or double lesions); (3) shape (patchy, large block, nodular, lumpy, honeycomblike or grid-like, cord-like, etc.); (4) density (mostly uneven, a paving stones-like change mixed with ground glass density and interlobular septal thickening, consolidation and thickened bronchial wall, etc.); and (5) concomitant signs vary (air-bronchogram, rare pleural effusion and mediastinal lymph nodes enlargement, etc.). Typical CT/X-ray imaging manifestation, including (1) Multiple, patchy, sub-segmental or segmental groundglass density shadows in both lungs. They were classified as "paving stone-like" changes by fine-grid or small honeycomb-like thickening of interlobular septa. The thinner the CT scan layers, the clearer the ground-glass opacity and thickening of interlobular septa were displayed. A slightly high-density and ground-glass change with fuzzy edge in the fine-grid or small honeycomb-like thickening of interlobular septa were presented by the high-resolution computed tomography (HRCT), ( Fig. 1: 45 cases, 54.2% in a total of 83 cases). The resolution of X-ray was worse lower than that of CT in the resolution, which was basically manifested as ground-glass When coughing or sneezing, it is necessary to wear a medical mask, or cover with a paper towel and bent elbow, and clean hands immediately after coughing and sneezing. Strong 10 N95 masks should be worn in the same room with patients (preferred strategy). Disposable surgical mask (alternative strategy). Use the mask in strict accordance with the instruction manual. After washing hands with running water, dry them with a paper towel (preferred strategy). Dry with a towel, and wash and disinfect the towel daily (alternative strategy). Home caregivers 1 Clean and disinfect hands after contact with the patient, before leaving patient's room or the house, before and after eating, after using the toilet and after entering house from outside (for visible contaminant on hands, wash hands with running water then use hand disinfection). Avoid direct contact with patient's secretions or discharges, especially oral or respiratory discharges; avoid direct contact with patient's feces. (2) Multiple, patchy or large patches of consolidation in both lungs, with a little grid-like or honeycombshaped interlobular septal thickening, especially in the middle and lower lobes ( Fig. 3: 26 cases, 31.3% in a total of 83 cases). It was more common in the elderly or severe condition patients. Atypical CT/X-ray imaging manifestation, including (1) Single, or multiple, or extensive subpleural grid-like or honeycomb-like thickening of interlobular septum, thickening of the bronchial wall, and tortuous and thick strand-like opacity. Several patchy consolidations, occasionally with a small amount pleural effusion or enlargement of mediastinal lymph nodes, can be seen ( Fig. 4 : 6 cases, 7.2% in a total of 83 cases). This is mostly seen in the elderly. (2) Single or multiple solid nodules or consolidated nodules in the center of lobule, surrounded by ground-glass opacities ( Fig. 5 : 5 cases, 6.2% in a total of 83 cases). Stage based on CT image The CT imaging demonstrates 5 stages according to the time of onset and the response of body to the virus, including: (1) Ultra-early stage. This stage usually refers to the stage of patients without clinical manifestation, negative laboratory test but positive throat swab for 2019-nCoV (2) Early stage.This stage refers to the period of 1-3 days after clinical manifestations (fever, cough, dry cough, etc.). The pathological process during this stage is dilatation and congestion of alveolar septal capillary, exudation of fluid in alveolar cavity and interlobular interstitial edema. It showed that single or multiple scattered patchy or agglomerated ground-glass opacities, separated by honeycomb-like or grid-like thickened of interlobular septa ( Fig. 7 : 45 cases, 54.2% in a total of 83 cases). It mainly should be distinguished from other known viral virus of pneumonia, such as influenza viruses, parainfluenza virus, adenovirus, respiratory syncytial virus, rhinovirus, human metapneumovirus, SARSr-CoV, etc.; and also from mycoplasma pneumonia, chlamydia pneumonia, and bacterial pneumonia. In addition, it should be distinguished from non-infectious diseases, such as vasculitis, dermatomyositis, and organizing pneumonia. In the early stage of the disease, the total number of leukocytes decreased or keeps normal, with decreased lymphocyte count or increased or normal monocytes. High attention should be paid on the situation where the absolute value of lymphocyte is less than 0.8 × 10 9 /L, or the numbers of CD4 and CD8 T cells are significantly decreased, which generally recommend rechecking the blood routine changes after 3 days. (1) Flu antigens. At present, routinely detected flu antigens are A, B, and H7N-subtypes. Sampling of throat swabs is conducive to early rapid screening for flu because of the fast test, but it has a relatively high false negative rate. (2) Respiratory virus nucleic acid. The detection of respiratory virus nucleic acid is commonly used to In the early stage of this disease, the total number of leukocytes in peripheral blood was normal or decreased, and the lymphocyte count decreased. In some patients, liver enzyme (transaminase), creatine kinase (CK) and myoglobin increased. CRP, ESR, and IL-6 increased, and PCT was normal in most patients. The increased Ddimer occurred in severe cases. Compared with 120 healthy check-ups, the absolute value of lymphocyte (0.87 vs 2.13) × 10 9 /L, lymphocyte percentage (19.5% vs 33.7%), eosinophil percentage (0.13% vs 2.16%), and absolute value (0.0061 vs 0.1417) × 10 9 /L in 2019-nCoV patients were significantly reduced (P < 0.05). The absolute number (4.2 vs 3.7) × 10 9 /L and the percentage (72.0% vs 57.0%) increased in 2019-nCoV patients (P < 0.05). The percentage of monocytes increased slightly (8.1% vs 6.8%), while the absolute number of monocytes did not change significantly (0.38 vs 0.44) × 10 9 /L. The next generation sequencing (NGS) and electron microscope technology play a role in the early diagnosis, but their diagnostic values have been weakened by the discovery of specific nucleic acid detection technology. In addition, NGS detection can tell whether the pathogen has mutated or not. Suspected and confirmed cases need to be treated in designated hospitals with effective isolation and protection conditions. Suspected cases need to be treated separately in single room, confirmed cases are admitted to a same ward, and critical cases should be admitted to ICU as soon as possible. (1) The patient should rest in bed, being monitored for vital signs (heart rate, pulse oxygen saturation, respiratory rate, blood pressure) and given supportive treatment to ensure sufficient energy intake and balance for water, electrolytes, acidbase levels and other internal environment factors (Strong recommendation). (2) The patient should be monitored for blood routine, CRP, PCT, organ function (liver enzyme, bilirubin, myocardial enzyme, creatinine, urea nitrogen, Urine volume, etc.), coagulation function, arterial blood gas analysis and chest imaging (Strong recommendation). First, oxygen therapy is the choice for patients with severe respiratory infections, respiratory distress, hypoxemia or shock. The initial flow rate is 5 L/min, and the titration flow rate is to reach the target oxygen saturation (adults: SpO 2 ≥ 90% in non-pregnant patients, SpO 2 ≥ 92-95% in pregnant patients; children: SpO 2 ≥ 94% in children with obstructive dyspnea, apnea, severe respiratory distress, central cyanosis, shock, coma or convulsions, and ≥ 90% in other children). Second, respiratory support should be given to patients with hypoxic respiratory failure and acute respiratory distress syndrome. HFNO or NIV can be selected when nasal cannula or mask oxygen therapy was ineffective or the patient had hypoxic respiratory failure. However, when patients had hypercapnia (acute exacerbation of chronic obstructive pulmonary disease, cardiogenic pulmonary edema), hemodynamic instability, multiple organ failure, and abnormal mental status HFNO oxygen is not the routinely adopted measure. If respiratory failure cannot be improved or worsens continuously within a short time (1 h) after using HFNO or NIV, intubation should be performed immediately. Low tidal volume (4-8 ml/kg) and low suction pressure (platform pressure < 30cmH 2 O) are used for invasive mechanical ventilation. It is suggested that positive endexpiratory pressure (PEEP) with high positive endexpiratory pressure should be used in patients with moderate or severe acute respiratory distress syndrome, and PEEP should be titrated according to FiO 2 to maintain SpO 2 , in order to improve alveolar atelectasis and reduce alveolar hyper-expansion and pulmonary vascular resistance at the end of inspiration. For severe patients with ARDS, it is recommended to ventilate in prone position for more than 12 h/d. should be considered for the patients with refractory hypoxemia that is difficult to be corrected by protective lung ventilation. (Strong recommendation). (1) At present, there is no evidence from RCT to support specific drug treatment against the new coronavirus in suspected or confirmed cases. (2) The α-interferon atomization inhalation can be considered (5 million U per time for adults in sterile injection water, twice a day) (Weak recommendation); lopinavir/ritonavir orally, 2 capsules each time, twice a day, can be also considered (Weak recommendation). Low-level evidences included retrospective cohort, historically controlled studies, case reports, and case series revealed that lopinavir/ritonavir alone or in combination with antivirals produced certain benefits in the treatment of SARS and MERS, such as reducing the incidence or mortality of ARDS [26] [27] [28] [29] . A recently systematic review showed that lopinavir/ritonavir's anti-coronavirus effect was mainly seen in its early application, for reducing patient mortality and reduced glucocorticoid consumption. However, if the early treatment window is missed, there will be no significant effect in their late application [30] . Real-world study stills need to further explore the clinical effects of its early use in 2019-nCoV infected pneumonia. The effectiveness of the combined use of antivirals is still controversial [31] [32] [33] [34] . (1) Principles. Avoid blind or inappropriate use of antibacterial drugs, especially the combination of broad-spectrum antibacterial drugs. Enhancement of bacteriological surveillance should be performed and promptly given appropriate antibacterial drugs when it occurs secondary bacterial infection. (2) According to the clinical manifestations of patients, if the accompanying bacterial infection cannot be ruled out, mild patients can take antibacterial drugs against community-acquired pneumonia, such as amoxicillin, azithromycin, or fluoroquinolones; empirical antibacterial treatment in severe patients should cover all possible pathogens, deescalating therapy until the pathogenic bacteria are clarified. The use of corticosteroids for severe ARDS is controversial; therefore, systemic use of glucocorticoids needs to be cautious. Methylprednisolone can be used as appropriate for patients with rapid disease progression or severe illness. According to the severity of the disease, 40 to 80 mg of methylprednisolone per day can be considered, and the total daily dose should not exceed 2 mg/kg (Weak recommendation). SARS management related researches showed that timely use of non-invasive continuous positive airway pressure and corticosteroids is an effective strategy for increased lung shadows and increased dyspnea. Appropriate use of glucocorticoids is able to significantly improve the clinical symptoms of patients with SARS, reduce the degree of disease progression, and accelerate the absorption of lung lesions; but it cannot shorten the length of hospital stay [35, 36] . Be cautious that hormone therapy has some incidence of adverse reactions [37] . (1) Symptomatic treatment of fever. When the temperature is higher than 38.5 ℃, ibuprofen can be used for Treat the patient based on syndrome differentiation individually. Prevention before illness is better than treatment after getting diseased. (1) Community. Implement relevant national regulations and take great effort to keep away from contaminated materials, disinfect the environment, and improve the healthcare management. i Fumigation with moxa in the room, 1-5 g/m 2 for 30 min per day. ii Wearing perfumed Chinese herb bags (clove, fineleaf schizonepeta herb, Perilla frutescens, atractylodes lancea, cinnamon, biond magnolia flower, asarum sieboldii, and Elettaria cardamomum, 2 g for each, crushed into powder and put it into bags for external use, change a new one every 10 days). iii Prescription of Chinese herbs for feet bath (vulgaris 10 g, carthamus 10 g, and dried ginger 6 g) Soaking the herbs in boiling water and bath the feet into the medical liquid when the temperature is suitable. Soak feet for about 20 min. iv Prescription of Chinese herbs for prophylaxis: Astragalus mongholicus 12 g, roasted rhizoma atractylodis macrocephalae 10 g, saposhnikovia divaricata 10 g, Cyrtomium fortunei 10 g, honeysuckle 10 g, dried tangerine or orange peel 6 g, eupatorium 10 g, and licorice 10 g. Taking the medicine above yielded decoction once a day for adults, and for 5 days as a treatment course. If for children, cutting the dose to half. v Medical tea: perilla leaf 6 g, agastache leaf 6 g, dried tangerine or orange peel 9 g, stewed amomum tsao-ko 6 g, and 3 slices of ginger. Soak the herbs in hot water and drink the water just like enjoying the tea. vi Chinese patent medicine: Huoxiang Zhengqi capsule or Huoxiang Zhengqi Shui (in half dose). In medical observation period There are two clinical symptoms in this period, including: (1) Clinical symptoms 1: hypodynamia accompanied by gastrointestinal upset. And the recommended Chinese patent medicine is the Huoxiang Zhengqi capsules (ball, liquid, or oral liquid). (2) Clinical symptoms 2: hypodynamia and fever. And the recommended Chinese patent medicines is the Jinhua Qinggan granules, Lianhua Qingwen capsules (granules), Shufeng Jiedu capsules (granules), or Fangfeng Tongsheng pills (granules). Clinical treatment period This period involving 7 stages, including: (1) Early-stage, characterized as exterior syndrome of cold-dampness. In this stage, the clinical manifestations presents as follow: aversion to cold without sweating, headache and generalized heaviness, limb pain, glomus and fullness in the chest and diaphragm, thirst with no desire to drink, ungratifying loose stool, yellow urine, frequent micturition and yellow urine. The therapeutic logic is to dissipate cold and eliminate dampness. And the recommended prescription is the Huoxiang Zhengqi powder (Yin dampness injuring superficies case from the National Famous Traditional Chinese Medical Doctor Medical Cases); which comprises of perilla leaf 10 g, atractylodes lancea 15 g, radix angelicae dahuricae 10 g, dried tangerine or orange peel 10 g, notopterygium root 10 g, agastache rugosus 10 g (end addition), mangnolia officinalis 10 g, saposhnikovia divaricata 10 g, poria peel 15 g, and Tetrapanax papyriferus 10 g above yielded decoction. In addition, the recommended Chinese patent medicine is Huoxiang Zhengqi capsules or Huoxiang Zhengqi Shui. (2) Early-stage, characterized as cold-dampness obstructing lung. In this stage, the clinical manifestations presents as follow: aversion to cold with or without fever, dry cough, dry throat, fatigue and hypodynamia, oppression in chest, epigastric fullness, or nausea, loose stool. The tongue is pale or reddish, the tongue fur is slimy white, and soggy pulse. Hence, the therapeutic logic is to dissipate cold and resolve obstruction. And the recommended prescriptions comprises of atractylodes lancea 15 g, dried tangerine or orange peel 10 g, mangnolia officinalis 10 g, agastache rugosus 10 g (end addition), amomum tsao-ko 6 g, ephedra herb 6 g, notopterygium root 10 g, ginger 10 g, areca-nut 10 g (end addition), periostracum cicada 10 g, bombyx batryticatus 10 g, and rhizoma curcumae longae 10 g above yielded decoction. (3) Middle-stage, characterized as epidemic toxin blocking the lung. In this stage, its clinical manifestations includes persistent fever or alternating cold and heat, cough with less phlegm, or yellow phlegm, abdominal distension and constipation; oppression in chest with anhelation, cough with wheezes, panting on exertion; or red tongue, slimy yellow fur or yellow dry fur, slippery and rapid pulse. Therefore, the therapeutic logic is clearing heat and detoxicating. And the recommended prescription comprises of almond 10 g, gypsum 30 g (predecoction), trichosanthes kirilowii 30 g, rhubarb 6 g (end addition), ephedra with honey fried 6 g, semen lepidii 10 g, peach kernel 10 g, amomum tsao-ko 6 g, arecanut 10 g, and atractylodes lancea 10 g above yielded decoction. In addition, the recommended Chinese patent medicine is Xiyanping injection or Xuebijing injection. (4) Severe stage, characterized as heat toxin generating stasis. In this stage, the clinical manifestations is known as high fever, oppression in chest with anhelation, purple-black facial complexion, lips dark and swollen, obnubilation, crimson tongue, yellow dry fur, surging and fine rapid stringlike pulse. Thus, its therapeutic logic is detoxicating and dispersing blood stasis. The recommended prescription is three Yellows and Gypsum decoction, Shang Jiang Powder, and Toxin-Resolving Blood-quickening decoction. Its composition comprises of ephedra with honey fried 10 g, almond 10 g, gypsum 20-30 g, periostracum cicada 10 g, bombyx batryticatus 10 g, rhizoma curcumae longae 10 g, rhubarb stir-fried with wine 10 g, scutellaria baicalensis 10 g, coptis chinensis 5 g, phillyrin 15 g, angelica sinensis 10 g, peach kernel 10 g, radix paeoniae rubra 15 g, and rhizome of rehmannia 15 g above yielded decoction. The recommended Chinese patent medicines is the Xiyanping injection, Xuebijing injection, Qingkailing injection, or Angong Niuhuang pills. (5) Severe-stage, characterized as inner blocking causing collapse. In this stage, the clinical manifestations include dyspnea, panting on exertion or need assisted ventilation, accompanied by coma, and agitation, cold limbs with cold sweating, dark purple tongue, thick or dry thick tongue fur, floating and rootless pulse. The thrapeutic logic is rescuing from collapse by restoring Yang. Hence, the recommended prescription comprises of ginseng 15 g, aconitine 10 g (predecoction), and Cornus officinalis 15 g above yielded decoction, and both taken with fluid Suhexiang pills or Angong Niuhuang pills. The recommended Chinese patent medicines is Xuebijing injection, Shenfu injection, or Shengmai injection. (6) Recovery-stage, presents as lung and spleen Qi deficiency. Its clinical manifestations include shortness of breath, fatigue and hypodynamia, anorexia, nausea and vomiting, glomus and fullness, weak stools, ungratifying loose stool, pale tender-soft enlarged tongue, slimy white tongue fur. Therefore, therapeutic logic is to supplement the spleen and lung. The recommended prescription comprises of rhizoma pinellinae praeparata 9 g, dried tangerine or orange peel 10 g, Codonopsis pilosula 15 g, radix astragali preparata 30 g, poria cocos 15 g, agastache rugosus 10 g, and fructus amomi 6 g (end addition) above yielded decoction. In addition, the recommended Chinese patent medicines is pill of costus and amomum with six noble ingredients. (7) Recovery-stage, characterized as deficiency of Qi and Yin. The clinical manifestations of this stage is generalized heat with sweating, chest heat vexation, Qi counterflow with retching and vomiting, shortness of breath and lassitude of essence-spirit, red tongue and thin tongue fur, vacuous pulse. Hence, the therapeutic logics is boost Qi and nourish Yin. The recommended prescription is Zhuye Shigao decoction with cogongrass rhizome and rhizoma phragmitis; and the composition of this prescription includes bamboo leaf 15 g, gypsum 15 g (predecoction), Codonopsis pilosula 15 g, radix ophiopogonis 10 g, pinellia ternate 9 g, cogongrass rhizome 15-30 g, rhizoma phragmitis 20 g, licorice 10 g, and polished round-grained rice 30 g above yielded decoction. The recommended Chinese patent medicine: Shengmaiyin. 6.5 Treatment of severe patients 6.5.1 Hypoxemic respiratory failure and ARDS treatments Treatment principle: treat the patients to improve the symptoms and underlying diseases, actively prevent potential complications and secondary infection; provide timely measures to support organ function. (1) Hypoxic respiratory failure and severe ARDS. Give oxygen therapy immediately to patients with ARDS, and closely monitor them for signs of clinical deterioration, such as rapidly progressive respiratory failure. Consider severe hypoxemic respiratory failure when standard oxygen therapy fails. Conservative fluid management can be adopted for ARDS patients without tissue hypoperfusion. Use vasoactive drugs to improve microcirculation. Empirical antibiotics targeting the suspected potential infection should be used as soon as possible, blind or improper combination of broad-spectrum antibiotics should be avoided. Unless for special reasons, the routine use of corticosteroids should be avoided. Glucocorticoids can be used in a short time (3-5 days) according to the degree of dyspnea and the progress of chest imaging if appropriate and the recommended dose is not more than the equivalent to 1-2 mg/kg methylprednisone per day. Provide intensive standard supportive care to the critically ill patients, including prevention of deep vein thrombosis and stress-induced gastrointestinal bleeding, blood glucose control and so on. Enteral nutrition can be provided. Supplemental nutrition with omega-3 fatty acids and antioxidants is not recommended. Inhaled or intravenous beta-adrenergic agonists are not recommended to promote alveolar fluid clearance and resolution of pulmonary edema. (1) Recognize the septic shock. When infection is suspected or confirmed, and on the basis of full fluid resuscitation, vasoconstrictor drugs are still needed to maintain mean arterial pressure (MAP) ≥65 mmHg with lactate ≥2 mmol/L, the existence of septic shock should be considered. If lactate cannot be monitored for some reasons, the following three manifestations (changes in mental state, oliguria, poor peripheral perfusion and prolonged capillary filling time) should be considered as signs of a combination of infection and hypoperfusion. (2) In resuscitation from septic shock in adults, at least 30 ml/kg of isotonic crystalloid was considered for adults in the first 3 h. In resuscitation from septic shock in children, give 20 ml/kg as a rapid bolus and up to 40-60 ml/kg in first aid. (3) Isosmotic crystal solution is recommended for resuscitation. Do not use hypotonic crystalloids, starches, or gelatins for resuscitation in the first hour. Albumin may be considered as a resuscitation fluid, but this recommendation was based on low-quality evidence under certain conditions. (4) Administer vasoconstrictor is suggested when shock persists after fluid resuscitation, noradrenaline as the first choice. The initial blood pressure target is MAP ≥65 mmHg in adults and age-appropriate targets in children. can also be administered via intraosseous needles. 6.6 Condition evaluation and treatment effect evaluation 6.6.1 Criteria to withdraw ECLS (1) Remove VV-ECMO. The oxygen concentration of the ECMO air-oxygen mixer has dropped to 21%, the air flow rate has dropped to 0, and the ventilator is not strong enough. Lasting for 2-3 h, the respiratory rate is within 25 breaths/min, SpO 2 > 92%, PaCO 2 is normal, and withdrawal from VV-ECMO may be considered. (2) Remove VA-ECMO. The blood flow rate is reduced to the rate of (0.2 to 0.5 L / min) every 5 to 6 h from 3 L/min, and the hemodynamic condition is stable. The blood flow rate is reduced to 1.5 L/min within 24 h. If there is a bridging tube, the arteriovenous end can be connected with a bridging tube to form an ECMO circuit for self-circulation, so that the body's hemodynamics is driven by the heart. If hemodynamics is stable for at least 6 h, consider removing the machine. When the patient is well aware, cough reflexes are obvious when sucking the sputum, the hemodynamics is stable, and the ventilator parameters are close to offline parameters, the spontaneous breathing test (SBT) is performed. After the SBT is passed, invasive breathing can be considered to remove the endotracheal tube. Patients do not need advanced respiratory support (HFNO, NIV, MV, ECLS, etc.); stable hemodynamics and tissue perfusion; no significant impairment of organ function; and no need for organ support treatment (CRRT, artificial liver, etc.). Consider transferring the patient out of ICU procedure. The body temperature returned to normal for more than 3 days; respiratory symptoms improved significantly; inflammation of the lungs showed obvious signs of absorption; and respiratory nucleic acid was negative for two consecutive times (one-day sampling time interval at least); and the patient can be released from isolation. 7 Prevent and control nosocomial infection 7.1 Restriction and isolation guidelines for patient/ suspected patients See Table 7 . (Strong recommendation). According to the principles of standard prevention and tertiary protection, all personnel entering various zones should be evaluated using individual inventory tables according to the exposure risk level. Chose personal protective equipment of various levels is necessary. Personal protective equipment should be worn strictly in accordance with the instructions and only used for one time ( The patient's home isolation scheme is shown in Table 5 . Patients should monitor their body temperature and illness at home. If your body temperature continues to be higher than 38 ℃, or your breath is getting worse, you should seek medical treatment timely. In addition to taking protective measures, the home caregivers also should monitor their body temperature closely. Mild patients generally use a nasal catheter and a mask for oxygen. Adjust the oxygen flow as appropriate according to the patient's condition and doctor's instruction, and Requirements to the medical staff request 6. Medical personnel enter the isolation area with proper self-protection through designated channels. 6.1 Medical staff should perform the personal protection practice under the Personal Protection Guidelines in Table 8 closely monitor the patient's breathing and blood oxygen saturation. If oxygen therapy fails to reach the expected effect, the nurse should analyze the cause comprehensively and be vigilant to notify the doctor. Mild patients generally use antiviral drugs, antibacterial drugs (when bacterial infection exists), and symptomatic treatment. The doctor's advice should be followed accurately and timely. The adverse reactions of oseltamivir mainly include nausea, vomiting, diarrhea, abdominal pain and bronchitis, cough, etc. The adverse reactions of interferon are mainly flu-like symptoms such as fever, fatigue, myalgia, and headache, followed by mild suppression of bone marrow. Attention should be paid to identify the change of clinical manifestations or adverse drug reactions. According to the patients' condition, provide highprotein, high-vitamin, carbohydrate-containing diets (e.g. eggs, fish, lean meat, milk, etc.) for enough nutrition to improve physical condition. Take good care of the patient and respond to the patient's question timely. Positively encourage patients to reduce their anxiety and fear. Dynamically monitor patients' vital signs, waterelectrolytes balance, acid-base balance, and functions of various organs, monitor patients' infection indicators, and determine the occurrence of complications such as acute respiratory distress syndrome, septic shock, stress ulcers, and deep vein thrombosis. The critically illed patients mainly use oxygen therapy such as HFNO, NIV and invasive mechanical ventilation. When using various oxygen treatments in a sequential manner, the airway and breathing circuit need to be kept open, and the effect of oxygen treatment needs to be monitored dynamically. At the same time, skincare products need to be used reasonably to avoid damage to the nose, face and lips by pressure. When using a high-flow nasal catheter to inhale oxygen, the oxygen flow and temperature and humidity should be adjusted appropriately. When using non-invasive mechanical ventilation, patient should receive relevant health education. Patients are instructed to inhale through the nose. The pressure is set from low to high and gradually reaches the target value. The human-machine coordination is maximized. The patient's consciousness and respiratory function are closely observed. Patients with artificial airway established should use a closed suction tube to reduce virus spread. Nurses should wear goggles or a face shield to avoid occupational exposure. If the patient develops moderate to severe ARDS, invasive mechanical ventilation combined with a prone position need to be adopted. Standard operating procedure for prone position needs to be followed. At the same time, be cautious to prevent pressure ulcers, falling bed, tube slippage, and eye damage by pressure and other complications. Patients treated with ECMO should be monitored for the performance of the oxygenator. If the oxygenator changes its color to darker, indicating the possibility of coagulation, the doctor should be notified to adjust the heparin dose as necessary. The oxygenator should be replaced if necessary. The coagulation function need to be monitored dynamically, including the whole set of coagulation and DIC (disseminated intravascular coagulation), and the time of activating partial thromboplastin, etc., the patient should be closely observed for signs of bleeding, such as bruising on the skin and mucous membranes, bleeding in the nasal cavity, oral cavity, bloody sputum, hematuria, blood in the stool, swelling of the abdomen, moving dullness, and the size of bilateral pupils. Make sure that the ECMO pipelines are tightly connected and firmly fixed to prevent air embolism and pipeline slippage. Perform oral care and skin care, assist the patient to use toilet, and take eyes on the indwelling tubes. Rules and regulations for aseptic operation and isolation should be strictly followed to prevent ventilator-related pneumonia, catheter-related sepsis, urinary catheter related urinary tract infections and other secondary infections. Dynamically assess the patients' nutritional risks and timely nutritional support can be given if needed. For the patients who can eat, the diet rich in protein and carbohydrates is recommended. Those patients who cannot eat but are compatible with enteral nutrition should be given enteral nutrition as soon as possible. For the patients incompatible with enteral nutrition, parenteral nutrition should be given timely to meet energy requirement. Psychological and humanistic care should be performed in high priority especially for the awake patients. Psychological techniques like mindfulness -based stress reduction can be adopted to relieve the patients' anxiety and panic by building up their optimistic confidence in overcoming the disease. Our guideline has three major limitations: Firstly, time is so limited that we cannot fully consider all clinical issues for this emergency disease. Secondly, many evidences came from data search is indirect. Thirdly, because some recommendations are based on the evidence from existing guidelines and experts' experience, there are situations where strong recommendations were produced on the base of low-quality evidence or very low-quality evidence, so high-quality evidence, when they appear, is likely to change current recommendations. Supplementary information accompanies this paper at https://doi.org/10. 1186/s40779-020-0233-6. Additional file 1. A successful treatment case of the severe 2019-nCoV infected pneumonia patient. Additional file 2. Experience and lessons in hospital rescue for 2019-nCoV infections. TB: tuberculosis; TNF: Tumor Necrosis Factor; WBC: White blood cells; WHO: World Health Organization	Where was COVID19 first discovered?	4,221	Wuhan, Hubei Province, China	2,778
2,651	Note from the editors: novel coronavirus (2019-nCoV) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988271/ SHA: d958168df85240e544a918d843a14e887dc41d2b Authors: nan Date: 2020-01-23 DOI: 10.2807/1560-7917.es.2020.25.3.2001231 License: cc-by Abstract: nan Text: The situation has continued to evolve rapidly since then and just a few weeks later, as at 23 January, 614 laboratory-confirmed cases and 17 deaths have been reported [2] including some cases detected outside mainland China [3] . Meanwhile, on 7 January 2020, the novel coronavirus, currently named 2019-nCoV, was officially announced as the causative agent by Chinese authorities [3] . In order to support public health action, viral genome sequences were released by Chinese researchers on 10 January [4] and 2 days later, four further sequences were also made available on the Global Initiative on Sharing All Influenza Data (GISAID) (https://www.gisaid.org/). While more cases are being reported on a daily basis and there is evidence for some human-to-human transmission in China, a number of important questions remain unanswered. For example, there is no certainty about the source of the outbreak, the transmissibility of the virus as well as the clinical picture and severity of the disease. In this issue of Eurosurveillance, we are publishing two articles on different aspects of the newly emerged 2019-nCoV. One is a research article by Corman et al. on the development of a diagnostic methodology based on RT-PCR of the E and RdRp genes, without the need for virus material; the assays were validated in five international laboratories [5] . Before this publication, a description of the assays had already been made publically available on a dedicated WHO webpage [6] to support rapid development of laboratory testing capacities. The other is a rapid communication where researchers based in Hong Kong report on their attempt to estimate the severity among hospitalised cases of 2019-nCoV infection through modelling based on publically available information, mainly from Wuhan health authorities [7] . It also points out the need for more detailed information to make an informed evaluation of the situation as basis for public health decision-making. Today, the WHO Director-General Tedros Adhanom Ghebreyesus, taking into consideration the deliberations of the members of the International Health Regulations (IHR) Emergency Committee on 2019-nCoV in their second meeting, decided not to declare a public health emergency of international concern. International health organisations such as the European Centre for Disease Prevention and Control (ECDC) and the WHO are monitoring the situation and provide regular updates. ECDC has set up a dedicated webpage on which updates and risk assessments with focus on Europe are available: https://www.ecdc.europa.eu/en/ novel-coronavirus-china.	Where can published genomic sequences be found for the 2019-nCoV virus?	529	Global Initiative on Sharing All Influenza Data (GISAID) (https://www.gisaid.org/)	847
2,651	Note from the editors: novel coronavirus (2019-nCoV) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988271/ SHA: d958168df85240e544a918d843a14e887dc41d2b Authors: nan Date: 2020-01-23 DOI: 10.2807/1560-7917.es.2020.25.3.2001231 License: cc-by Abstract: nan Text: The situation has continued to evolve rapidly since then and just a few weeks later, as at 23 January, 614 laboratory-confirmed cases and 17 deaths have been reported [2] including some cases detected outside mainland China [3] . Meanwhile, on 7 January 2020, the novel coronavirus, currently named 2019-nCoV, was officially announced as the causative agent by Chinese authorities [3] . In order to support public health action, viral genome sequences were released by Chinese researchers on 10 January [4] and 2 days later, four further sequences were also made available on the Global Initiative on Sharing All Influenza Data (GISAID) (https://www.gisaid.org/). While more cases are being reported on a daily basis and there is evidence for some human-to-human transmission in China, a number of important questions remain unanswered. For example, there is no certainty about the source of the outbreak, the transmissibility of the virus as well as the clinical picture and severity of the disease. In this issue of Eurosurveillance, we are publishing two articles on different aspects of the newly emerged 2019-nCoV. One is a research article by Corman et al. on the development of a diagnostic methodology based on RT-PCR of the E and RdRp genes, without the need for virus material; the assays were validated in five international laboratories [5] . Before this publication, a description of the assays had already been made publically available on a dedicated WHO webpage [6] to support rapid development of laboratory testing capacities. The other is a rapid communication where researchers based in Hong Kong report on their attempt to estimate the severity among hospitalised cases of 2019-nCoV infection through modelling based on publically available information, mainly from Wuhan health authorities [7] . It also points out the need for more detailed information to make an informed evaluation of the situation as basis for public health decision-making. Today, the WHO Director-General Tedros Adhanom Ghebreyesus, taking into consideration the deliberations of the members of the International Health Regulations (IHR) Emergency Committee on 2019-nCoV in their second meeting, decided not to declare a public health emergency of international concern. International health organisations such as the European Centre for Disease Prevention and Control (ECDC) and the WHO are monitoring the situation and provide regular updates. ECDC has set up a dedicated webpage on which updates and risk assessments with focus on Europe are available: https://www.ecdc.europa.eu/en/ novel-coronavirus-china.	What genes have been targeted for the diagnostic RT-PCR tests in 2019-nCoV?	531	E and RdRp genes	1,501
1,559	COVID-19 and smoking: A systematic review of the evidence https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083240/ SHA: f4bde74efeb547d3d6d3f935482a80c9d456198f Authors: Vardavas, Constantine I.; Nikitara, Katerina Date: 2020-03-20 DOI: 10.18332/tid/119324 License: cc-by Abstract: COVID-19 is a coronavirus outbreak that initially appeared in Wuhan, Hubei Province, China, in December 2019, but it has already evolved into a pandemic spreading rapidly worldwide(1,2). As of 18 March 2020, a total number of 194909 cases of COVID-19 have been reported, including 7876 deaths, the majority of which have been reported in China (3242) and Italy (2505)(3). However, as the pandemic is still unfortunately under progression, there are limited data with regard to the clinical characteristics of the patients as well as to their prognostic factors(4). Smoking, to date, has been assumed to be possibly associated with adverse disease prognosis, as extensive evidence has highlighted the negative impact of tobacco use on lung health and its causal association with a plethora of respiratory diseases(5). Smoking is also detrimental to the immune system and its responsiveness to infections, making smokers more vulnerable to infectious diseases(6). Previous studies have shown that smokers are twice more likely than non-smokers to contract influenza and have more severe symptoms, while smokers were also noted to have higher mortality in the previous MERS-CoV outbreak(7,8). Given the gap in the evidence, we conducted a systematic review of studies on COVID-19 that included information on patients’ smoking status to evaluate the association between smoking and COVID-19 outcomes including the severity of the disease, the need for mechanical ventilation, the need for intensive care unit (ICU) hospitalization and death. The literature search was conducted on 17 March 2020, using two databases (PubMed, ScienceDirect), with the search terms: [‘smoking’ OR ‘tobacco’ OR ‘risk factors’ OR ‘smoker*’] AND [‘COVID-19’ OR ‘COVID 19’ OR ‘novel coronavirus’ OR ‘sars cov-2’ OR ‘sars cov 2’] and included studies published in 2019 and 2020. Further inclusion criteria were that the studies were in English and referred to humans. We also searched the reference lists of the studies included. A total of 71 studies were retrieved through the search, of which 66 were excluded after full-text screening, leaving five studies that were included. All of the studies were conducted in China, four in Wuhan and one across provinces in mainland China. The populations in all studies were patients with COVID-19, and the sample size ranged from 41 to 1099 patients. With regard to the study design, retrospective and prospective methods were used, and the timeframe of all five studies covered the first two months of the COVID-19 pandemic (December 2019, January 2020). Specifically, Zhou et al.(9) studied the epidemiological characteristics of 191 individuals infected with COVID-19, without, however, reporting in more detail the mortality risk factors and the clinical outcomes of the disease. Among the 191 patients, there were 54 deaths, while 137 survived. Among those that died, 9% were current smokers compared to 4% among those that survived, with no statistically significant difference between the smoking rates of survivors and non-survivors (p=0.21) with regard to mortality from COVID-19. Similarly, Zhang et al.(10) presented clinical characteristics of 140 patients with COVID-19. The results showed that among severe patients (n=58), 3.4% were current smokers and 6.9% were former smokers, in contrast to non-severe patients (n=82) among which 0% were current smokers and 3.7% were former smokers , leading to an OR of 2.23; (95% CI: 0.65–7.63; p=0.2). Huang et al.(11) studied the epidemiological characteristics of COVID-19 among 41 patients. In this study, none of those who needed to be admitted to an ICU (n=13) was a current smoker. In contrast, three patients from the non-ICU group were current smokers, with no statistically significant difference between the two groups of patients (p=0.31), albeit the small sample size of the study. The largest study population of 1099 patients with COVID-19 was provided by Guan et al.(12) from multiple regions of mainland China. Descriptive results on the smoking status of patients were provided for the 1099 patients, of which 173 had severe symptoms, and 926 had non-severe symptoms. Among the patients with severe symptoms, 16.9% were current smokers and 5.2% were former smokers, in contrast to patients with non-severe symptoms where 11.8% were current smokers and 1.3% were former smokers. Additionally, in the group of patients that either needed mechanical ventilation, admission to an ICU or died, 25.5% were current smokers and 7.6% were former smokers. In contrast, in the group of patients that did not have these adverse outcomes, only 11.8% were current smokers and 1.6% were former smokers. No statistical analysis for evaluating the association between the severity of the disease outcome and smoking status was conducted in that study. Finally, Liu et al.(13) found among their population of 78 patients with COVID-19 that the adverse outcome group had a significantly higher proportion of patients with a history of smoking (27.3%) than the group that showed improvement or stabilization (3.0%), with this difference statistically significant at the p=0.018 level. In their multivariate logistic regression analysis, the history of smoking was a risk factor of disease progression (OR=14.28; 95% CI: 1.58–25.00; p= 0.018). We identified five studies that reported data on the smoking status of patients infected with COVID-19. Notably, in the largest study that assessed severity, there were higher percentages of current and former smokers among patients that needed ICU support, mechanical ventilation or who had died, and a higher percentage of smokers among the severe cases(12). However, from their published data we can calculate that the smokers were 1.4 times more likely (RR=1.4, 95% CI: 0.98–2.00) to have severe symptoms of COVID-19 and approximately 2.4 times more likely to be admitted to an ICU, need mechanical ventilation or die compared to non-smokers (RR=2.4, 95% CI: 1.43–4.04). In conclusion, although further research is warranted as the weight of the evidence increases, with the limited available data, and although the above results are unadjusted for other factors that may impact disease progression, smoking is most likely associated with the negative progression and adverse outcomes of COVID-19. Text: non-survivors (p=0.21) with regard to mortality from COVID-19. Similarly, Zhang et al. 10 presented clinical characteristics of 140 patients with COVID-19. The results showed that among severe patients (n=58), 3.4% were current smokers and 6.9% were former smokers, in contrast to non-severe patients (n=82) among which 0% were current smokers and 3.7% were former smokers , leading to an OR of 2.23; (95% CI: 0.65-7.63; p=0.2). Huang et al. 11 studied the epidemiological characteristics of COVID-19 among 41 patients. In this study, none of those who needed to be admitted to an ICU (n=13) was a current smoker. In contrast, three patients from the non-ICU group were current smokers, with no statistically significant difference between the two groups of patients (p=0.31), albeit the small sample size of the study. The largest study population of 1099 patients with COVID-19 was provided by Guan et al. 12 from multiple regions of mainland China. Descriptive results on the smoking status of patients were provided for the 1099 patients, of which 173 had severe symptoms, and 926 had non-severe symptoms. Among the patients with severe symptoms, 16.9% were current smokers and 5.2% were former smokers, in contrast to patients with non-severe symptoms where 11.8% were current smokers and 1.3% were former smokers. Additionally, in the group of patients that either needed mechanical ventilation, admission to an ICU or died, 25.5% were current smokers and 7.6% were former smokers. In contrast, in the group of patients that did not have these adverse outcomes, only 11.8% were current smokers and 1.6% were former smokers. No statistical analysis for evaluating the association between the severity of the disease outcome and smoking status was conducted in that study. Finally, Liu et al. 13 found among their population of 78 patients with COVID-19 that the adverse outcome group had a significantly higher proportion of patients with a history of smoking (27.3%) than the group that showed improvement or stabilization (3.0%), with this difference statistically significant at the p=0.018 level. In their multivariate logistic regression analysis, the history of smoking was a risk factor of disease progression (OR=14.28; 95% CI: 1.58-25.00; p= 0.018). We identified five studies that reported data on the smoking status of patients infected with COVID-19. Notably, in the largest study that assessed severity, there were higher percentages of current and former smokers among patients that needed ICU support, mechanical ventilation or who had died, and a higher percentage of smokers among the severe cases 12 . However, from their published data we can calculate that the smokers were 1.4 times more likely (RR=1.4, 95% CI: 0.98-2.00) to have severe symptoms of COVID-19 and approximately 2.4 times more likely to be admitted to an ICU, need mechanical ventilation or die compared to non-smokers (RR=2.4, 95% CI: 1.43-4.04). In conclusion, although further research is warranted as the weight of the evidence increases, with the limited available data, and although the above results are unadjusted for other factors that may impact disease progression, smoking is most likely associated with the negative progression and adverse outcomes of COVID-19.	How does being a smoker impact COVID-19 patient outcomes?	266	smokers were 1.4 times more likely (RR=1.4, 95% CI: 0.98–2.00) to have severe symptoms of COVID-19 and approximately 2.4 times more likely to be admitted to an ICU, need mechanical ventilation or die compared to non-smokers (RR=2.4, 95% CI: 1.43–4.04)	6,018
1,559	COVID-19 and smoking: A systematic review of the evidence https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083240/ SHA: f4bde74efeb547d3d6d3f935482a80c9d456198f Authors: Vardavas, Constantine I.; Nikitara, Katerina Date: 2020-03-20 DOI: 10.18332/tid/119324 License: cc-by Abstract: COVID-19 is a coronavirus outbreak that initially appeared in Wuhan, Hubei Province, China, in December 2019, but it has already evolved into a pandemic spreading rapidly worldwide(1,2). As of 18 March 2020, a total number of 194909 cases of COVID-19 have been reported, including 7876 deaths, the majority of which have been reported in China (3242) and Italy (2505)(3). However, as the pandemic is still unfortunately under progression, there are limited data with regard to the clinical characteristics of the patients as well as to their prognostic factors(4). Smoking, to date, has been assumed to be possibly associated with adverse disease prognosis, as extensive evidence has highlighted the negative impact of tobacco use on lung health and its causal association with a plethora of respiratory diseases(5). Smoking is also detrimental to the immune system and its responsiveness to infections, making smokers more vulnerable to infectious diseases(6). Previous studies have shown that smokers are twice more likely than non-smokers to contract influenza and have more severe symptoms, while smokers were also noted to have higher mortality in the previous MERS-CoV outbreak(7,8). Given the gap in the evidence, we conducted a systematic review of studies on COVID-19 that included information on patients’ smoking status to evaluate the association between smoking and COVID-19 outcomes including the severity of the disease, the need for mechanical ventilation, the need for intensive care unit (ICU) hospitalization and death. The literature search was conducted on 17 March 2020, using two databases (PubMed, ScienceDirect), with the search terms: [‘smoking’ OR ‘tobacco’ OR ‘risk factors’ OR ‘smoker*’] AND [‘COVID-19’ OR ‘COVID 19’ OR ‘novel coronavirus’ OR ‘sars cov-2’ OR ‘sars cov 2’] and included studies published in 2019 and 2020. Further inclusion criteria were that the studies were in English and referred to humans. We also searched the reference lists of the studies included. A total of 71 studies were retrieved through the search, of which 66 were excluded after full-text screening, leaving five studies that were included. All of the studies were conducted in China, four in Wuhan and one across provinces in mainland China. The populations in all studies were patients with COVID-19, and the sample size ranged from 41 to 1099 patients. With regard to the study design, retrospective and prospective methods were used, and the timeframe of all five studies covered the first two months of the COVID-19 pandemic (December 2019, January 2020). Specifically, Zhou et al.(9) studied the epidemiological characteristics of 191 individuals infected with COVID-19, without, however, reporting in more detail the mortality risk factors and the clinical outcomes of the disease. Among the 191 patients, there were 54 deaths, while 137 survived. Among those that died, 9% were current smokers compared to 4% among those that survived, with no statistically significant difference between the smoking rates of survivors and non-survivors (p=0.21) with regard to mortality from COVID-19. Similarly, Zhang et al.(10) presented clinical characteristics of 140 patients with COVID-19. The results showed that among severe patients (n=58), 3.4% were current smokers and 6.9% were former smokers, in contrast to non-severe patients (n=82) among which 0% were current smokers and 3.7% were former smokers , leading to an OR of 2.23; (95% CI: 0.65–7.63; p=0.2). Huang et al.(11) studied the epidemiological characteristics of COVID-19 among 41 patients. In this study, none of those who needed to be admitted to an ICU (n=13) was a current smoker. In contrast, three patients from the non-ICU group were current smokers, with no statistically significant difference between the two groups of patients (p=0.31), albeit the small sample size of the study. The largest study population of 1099 patients with COVID-19 was provided by Guan et al.(12) from multiple regions of mainland China. Descriptive results on the smoking status of patients were provided for the 1099 patients, of which 173 had severe symptoms, and 926 had non-severe symptoms. Among the patients with severe symptoms, 16.9% were current smokers and 5.2% were former smokers, in contrast to patients with non-severe symptoms where 11.8% were current smokers and 1.3% were former smokers. Additionally, in the group of patients that either needed mechanical ventilation, admission to an ICU or died, 25.5% were current smokers and 7.6% were former smokers. In contrast, in the group of patients that did not have these adverse outcomes, only 11.8% were current smokers and 1.6% were former smokers. No statistical analysis for evaluating the association between the severity of the disease outcome and smoking status was conducted in that study. Finally, Liu et al.(13) found among their population of 78 patients with COVID-19 that the adverse outcome group had a significantly higher proportion of patients with a history of smoking (27.3%) than the group that showed improvement or stabilization (3.0%), with this difference statistically significant at the p=0.018 level. In their multivariate logistic regression analysis, the history of smoking was a risk factor of disease progression (OR=14.28; 95% CI: 1.58–25.00; p= 0.018). We identified five studies that reported data on the smoking status of patients infected with COVID-19. Notably, in the largest study that assessed severity, there were higher percentages of current and former smokers among patients that needed ICU support, mechanical ventilation or who had died, and a higher percentage of smokers among the severe cases(12). However, from their published data we can calculate that the smokers were 1.4 times more likely (RR=1.4, 95% CI: 0.98–2.00) to have severe symptoms of COVID-19 and approximately 2.4 times more likely to be admitted to an ICU, need mechanical ventilation or die compared to non-smokers (RR=2.4, 95% CI: 1.43–4.04). In conclusion, although further research is warranted as the weight of the evidence increases, with the limited available data, and although the above results are unadjusted for other factors that may impact disease progression, smoking is most likely associated with the negative progression and adverse outcomes of COVID-19. Text: non-survivors (p=0.21) with regard to mortality from COVID-19. Similarly, Zhang et al. 10 presented clinical characteristics of 140 patients with COVID-19. The results showed that among severe patients (n=58), 3.4% were current smokers and 6.9% were former smokers, in contrast to non-severe patients (n=82) among which 0% were current smokers and 3.7% were former smokers , leading to an OR of 2.23; (95% CI: 0.65-7.63; p=0.2). Huang et al. 11 studied the epidemiological characteristics of COVID-19 among 41 patients. In this study, none of those who needed to be admitted to an ICU (n=13) was a current smoker. In contrast, three patients from the non-ICU group were current smokers, with no statistically significant difference between the two groups of patients (p=0.31), albeit the small sample size of the study. The largest study population of 1099 patients with COVID-19 was provided by Guan et al. 12 from multiple regions of mainland China. Descriptive results on the smoking status of patients were provided for the 1099 patients, of which 173 had severe symptoms, and 926 had non-severe symptoms. Among the patients with severe symptoms, 16.9% were current smokers and 5.2% were former smokers, in contrast to patients with non-severe symptoms where 11.8% were current smokers and 1.3% were former smokers. Additionally, in the group of patients that either needed mechanical ventilation, admission to an ICU or died, 25.5% were current smokers and 7.6% were former smokers. In contrast, in the group of patients that did not have these adverse outcomes, only 11.8% were current smokers and 1.6% were former smokers. No statistical analysis for evaluating the association between the severity of the disease outcome and smoking status was conducted in that study. Finally, Liu et al. 13 found among their population of 78 patients with COVID-19 that the adverse outcome group had a significantly higher proportion of patients with a history of smoking (27.3%) than the group that showed improvement or stabilization (3.0%), with this difference statistically significant at the p=0.018 level. In their multivariate logistic regression analysis, the history of smoking was a risk factor of disease progression (OR=14.28; 95% CI: 1.58-25.00; p= 0.018). We identified five studies that reported data on the smoking status of patients infected with COVID-19. Notably, in the largest study that assessed severity, there were higher percentages of current and former smokers among patients that needed ICU support, mechanical ventilation or who had died, and a higher percentage of smokers among the severe cases 12 . However, from their published data we can calculate that the smokers were 1.4 times more likely (RR=1.4, 95% CI: 0.98-2.00) to have severe symptoms of COVID-19 and approximately 2.4 times more likely to be admitted to an ICU, need mechanical ventilation or die compared to non-smokers (RR=2.4, 95% CI: 1.43-4.04). In conclusion, although further research is warranted as the weight of the evidence increases, with the limited available data, and although the above results are unadjusted for other factors that may impact disease progression, smoking is most likely associated with the negative progression and adverse outcomes of COVID-19.	Are smokers more likely to contract influenza?	267	Previous studies have shown that smokers are twice more likely than non-smokers to contract influenza and have more severe symptoms, while smokers were also noted to have higher mortality in the previous MERS-CoV outbreak	1,245
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	Why might we underestimate the spread of COVID19?	2,185	limited information available regarding incubation time, transmissibility, and virus origin	3,118
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	Where was the first imported case of COVID19 in the United States?	2,186	Washington	4,564
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	When was the first case of COVID19 confirmed in the USA?	2,187	January 15, 2020	4,421
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	When was the second COVID19 case reported in the US?	2,188	January 24, 2020	4,723
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	Where was the second reported case of COVID in the United States?	2,189	Chicago	4,667
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	When was the first local transmission of COVID reported in the United States?	2,190	January 30, 2020	4,929
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	When did the WHO declare COVID to be a Public Health Emergency of International Concern?	2,191	January 30, 2020	4,929
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	When did the United States declare COVID19 a public health emergency?	2,192	January 31, 2020,	5,172
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	What are the most common symptoms of COVID19?	2,193	Fever and cough	6,790
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	What symptoms might people experience with COVID19?	2,194	patients with underlying medical conditions and the elderly	7,166
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	Who is at greater risk of dying from COVID19?	2,195	patients with underlying medical conditions and the elderly	7,166
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	How long is the incubation time for COVID19?	2,196	between 2 and 14 days	7,356
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	How does COVID19 get spread?	2,197	close contact with an infected person	11,444
2,668	2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/ SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2 Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C. Date: 2020-01-31 DOI: 10.5811/westjem.2020.1.46760 License: cc-by Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV. Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV. What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients. This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients. age distribution of these verified deaths is currently not available. One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies. Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24 By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time. With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question. While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms. Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread. It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission. The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred. Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35 Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV. Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated. Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization. Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads. As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted. The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted. Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures. Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40 2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers.	Is it possible to get infected with COVID and another virus?	2,198	Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV	14,067
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	How many people are estimated to need humanitarian assistance in 2020?	1,909	168 million people across 50 countries	369
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	For whom does the SARS-COV-2 pose a great threat?	1,910	those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response.	964
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What can undermine interventions?	1,911	Poor governance, public distrust, and political violence	1,096
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	Who are expected to be particularly susceptible?	1,912	Populations affected by humanitarian crises	1,209
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	Why populations may be particularly susceptible?	1,913	due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization	1,344
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What is the impact of disease outbreaks?	1,914	Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems.	1,472
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What represents a barrier to testing?	1,915	limited public health, laboratory, and primary care services	2,255
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	Where are difficulties are exacerbated during humanitarian crises?	1,916	Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain	2,349
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What can prevent contact tracing?	1,917	Frequent displacement and limited contact information	2,580
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What is an example of intractable structural challenge?	1,918	overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill.	2,725
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What should be the priority of the national and international bodies trying to prevent the pandemic?	1,919	increased vulnerabilities, humanitarian crises	2,847
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What resources need to be identified?	1,920	to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases.	3,037
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What is an effective public health hygiene?	1,921	Respiratory hygiene i	3,371
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What has been demonstrated to be effective for prevention?	1,922	hand hygiene, safe cough practice, and social distancing [	3,558
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What has increased hand washing?	1,923	the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30%	3,668
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What is hand washing to protect one's own health consistent with?	1,924	the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises.	3,888
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What is possible in many resource -limited settings?	1,925	Widespread introduction of alcohol-based hand rubs	3,994
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What is the foremost authority on minimum standards for humanitarian assistance?	1,926	The Sphere Handbook, a collection of rights-based guidelines for humanitarian response	4,150
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	For what there is evidence for the efficacy of hand washing?	1,927	reducing both bacterial and viral pathogen transmission,	4,398
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What are humanitarian WASH standards based on?	1,928	evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines	4,497
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What confers a high risk of gender based violence?	1,929	latrines in crisis settings are often shared and distant from residential shelters,	4,657
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What is the deterrent effect of gender based violence around latrines?	1,930	for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission.	4,858
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What will maximize the effectiveness of interventions?	1,931	Crisis-affected community engagement is integral in pandemic planning,	5,265
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What will happen without the adaptation of existing standards?	1,932	mitigation plans will fall short of health and human rights obligations in outbreak response	5,170
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What is essential when pandemics threaten vulnerable populations?	1,933	Transparent and credible information-sharing mechanisms	5,416
2,643	Responding to the COVID-19 pandemic in complex humanitarian crises https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/ SHA: d013e42811c6442b184da3b9bbfd9e334031a975 Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A. Date: 2020-03-21 DOI: 10.1186/s12939-020-01162-y License: cc-by Abstract: nan Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings. Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] . As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases. To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] . The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission. Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic.	What is a necessary component of effective health governance?	1,934	Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors	5,553
776	It is Unlikely That Influenza Viruses Will Cause a Pandemic Again Like What Happened in 1918 and 1919 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4019839/ Song, Liting 2014-05-07 DOI:10.3389/fpubh.2014.00039 License:cc-by Abstract: nan Text: Influenza and influenza viruses are wellknown popular topics to medical professionals and the general public. Influenza viruses had caused a pandemic globally during 1918 and 1919, and that influenza pandemic had taken away more than 20 million people's lives in the world. However, in my opinion, it is unlikely that influenza viruses will again cause a pandemic on a level (both of the morbidity rate and the mortality rate) comparable to what happened in 1918 and 1919. Influenza viruses very easily reassort, recombine, and point mutate in nature due to their segmented RNA genome structures, however, unlike highly pathogenic (virulent) viruses like rabies virus, Lassa fever virus, smallpox virus, eastern equine encephalitis virus, Ebola virus, Marburg virus, and human immunodeficiency virus 1 (HIV-1); most influenza viruses (wild types and mutants) are moderately pathogenic. The case fatality rates of some highly virulent viruses and related references are listed in Table 1 . On November 11, 1918 , the fighting of World War I was stopped, and World War I was officially ended on June 28, 1919 with the signing of the Versailles Treaty. It is estimated that around 8.5-10 million soldiers lost their lives in World War I due to battle. The war also directly caused more than 6 million civilian deaths. Millions of people suffered from hunger and malnutrition during the war. Malnutrition weakened the human immune system and made a person more vulnerable to infectious diseases like tuberculosis and influenza, therefore, hunger and malnutrition were indirectly responsible for millions of deaths in the world in that period of time. For example, about 700,000 Germans died from malnutrition-related diseases in the years of 1914-1918. During the 1918-1919 influenza pandemic, between 21 and 25 million people died of influenza worldwide. Those people were killed both directly and indirectly by influenza virus infections. Many families were too poor to buy food and coal, and to afford health care expenses when their family members were ill. Influenza virus could infect all members of a family, and this could result in no one left to feed the fires, and to prepare food for the whole family, even if they had firewood, coal, and food left in their homes. Sadly, a large number of people died of influenza virus infections along with starvation, cold, and poor living conditions (8) . In recent years, while hunger and malnutrition are not major and serious problems in some developed countries anymore, they are still very difficult to overcome in many developing countries. In these less-developed countries, there were approximately 925 million people who suffered from hunger; 125 million children were underweight; and 195 million children were stunted each year (9) . Nevertheless, in comparison to 1918 and 1919, currently, we have much better social and economic conditions and public health systems globally; and generally speaking, the majority of people in the world have better nutritional and educational statuses; better living and working conditions; therefore, better general health and immunity. Furthermore, in 1918 and 1919, physicians and nurses almost had nothing in their hands to help individuals who were infected by influenza viruses. Today, although we still do not have very effective, powerful, and practical anti-influenza drugs available, we at least have some improved, useful, and helpful anti-viral drugs like zanamivir, and effective, convenient anti-cold medicines like Tylenol or Advil. We do not have a universal vaccine to prevent all influenza virus infections, but we can make effective vaccines to a specific influenza virus strain in a short time. Actually, in the United States of America, the influenza classed mortality rate declined from 10.2/100,000 in the 1940s to 0.56/100,000 in the 1990s; and the classed mortality rates of 1957-1958 and 1968-1969 influenza pandemics were not remarkably different from the non-pandemic seasons (10) . Because of the above reasons, we can optimistically assume that even the same strain of influenza virus, which caused pandemic in 1918 and 1919, would not be able to kill millions of people and cause a pandemic comparable to the 1918-1919 pandemic again in the future. Additionally, a significant number of viruses can cause influenza-like syndromes, such as rhinovirus, parainfluenza virus, adenovirus, coronavirus, respiratory syncytial virus, Coxsackie B virus, echovirus, and metapneumovirus (11, 12) . Some of the above-mentioned viruses like adenovirus and mutated coronavirus could cause problems that are comparable to influenza viruses (13, 14) . The World Health Organization (WHO) mistakenly raised the level of influenza pandemic alert from phase 5 to the highest phase 6 on June 11, 2009 (15) . However, the truth was that most cases of H1N1 influenza A virus infections were mild, the symptomatic case fatality rate was only 0.005% in New Zealand (16) ; and in New York City, the case fatality rate was 0.0094-0.0147% for persons ≥65 years old, and for those of 0-17 years old, the case fatality rate was 0.0008-0.0012% (17) . Some researchers argued that it should not have been called an influenza pandemic in the first place if the clinical severity was considered (15, (18) (19) (20) . I believe it was unwise that we had paid too much www.frontiersin.org 23) . Not surprisingly, every year there would be some influenza patients and a few of them would die from the infections, as it is almost impossible to eliminate influenza viruses from the natural environment in many years. The severity of a viral infection is determined by both of the viral virulence (pathogenicity) and the host immunity. Some researchers' opinions on H7N9 avian influenza virus were incorrect and/or inadequate. They mainly focused on influenza viruses and worried about viral mutations, viral pathogenicity, viral adaptation, and transmission. They overestimated the negative part of socio-economic factors of the present east China: overcrowded population in the epidemic region; very busy national and international transportation and travel; a large number of live poultry markets . . . but they underestimated the currently changed, developed, and improved positive part of socio-economic factors in China. The following factors might be used to explain why that H7N9 influenza A virus epidemic was limited and controlled in China, and only a few immunocompromised patients were killed by H7N9 influenza A virus. First, China has a relatively organized and effective public health system, there are four levels of (national, provincial, prefectural-level city, and county) centers for disease control and prevention all over China (24) . Second, physicians and nurses in China were prepared and knowledgeable of influenza virus infections. Third, samples from patients with suspected influenza virus infections were collected and sent to the local and national centers for disease control and prevention promptly. H7N9 influenza A viruses were isolated and identified very quickly. Thereby, they were able to diagnose, confirm, and report three cases of H7N9 influenza patients in the early stage of the epidemic (24, 25) . Fourth, health care and public health workers were protected properly. Consequently, none of the health professionals was infected by H7N9 influenza A virus in 2013. However, a surgeon died of H7N9 influenza in Shanghai, China in January of 2014 (26) . Fifth, they detected H7N9 influenza A viruses from the samples of chickens, pigeons, and the environment of live poultry markets in Shanghai (27) ; and closed the live poultry markets of the involved epidemic region quickly. Sixth, patients were isolated and treated timely in hospitals, 74% (1251/1689) of those close contacts of H7N9 influenza patients were monitored and observed. Thus, H7N9 influenza A virus could not spread to a bigger population (24) . Last but not least, we are connected to the Internet now, and it seems that our planet is much smaller today than the earlier days when we did not have the Internet, because communication and information exchange have become so fast, easy, and convenient presently. During that avian influenza epidemic, some influenza experts in the world shared/exchanged H7N9 influenza A virus information and provided professional consultations and suggestions efficiently and rapidly. All these public health routine practices and measures resulted in that H7N9 influenza epidemic being controlled and stopped in China (24) . I have to point out that the cases of diagnosed H7N9 avian influenza A virus infection might only be the tip of the iceberg. Aside from one laboratory confirmed asymptotic case of H7N9 influenza A virus infection in Beijing (22), there were probably many undetected mild or asymptotic cases of influenza A H7N9 infection. The reason is that most people usually think a common cold is a very common and normal occurrence, and they don't take flu-like illnesses seriously. In most situations, they would just stay home and take some medicines. Only those who have very severe flu-like symptoms would see doctors, and thereby be detected and diagnosed, accordingly the real case fatality rate should be much lower than the detected 32.14% (45/140, one case from Taiwan, and one case from Hong Kong) (22, 23). Nowadays, we travel faster, and we travel more frequently and globally, and we have more complicated social activities and lifestyles, thereby increasing the chances of viral mutation; and we realize that influenza viruses are even easier to reassort, recombine, and mutate in nature than many other RNA viruses. However, we are now living in a technologically, economically, and socially much better and advanced society. I believe influenza virus infections are controllable and preventable, with the increased population health and immunity, with the WHO Global Influenza Surveillance and Response System, and with standard/routine epidemiological practices, and with new effective anti-viral agents and vaccines in production in the future. Now, I first predict that influenza viruses will unlikely again cause a pandemic on a level comparable to what happened in 1918 and 1919. Hopefully, one day we could consider a strategy to produce a universal vaccine that can prevent people from infections of all influenza virus strains, or we could produce some very effective anti-influenza virus drugs; then influenza would not be a problem anymore. We should learn lessons from the mistakes we made in the past. It is reasonable and necessary to be cautious about influenza viruses, but overreactions or catastrophic reactions should be avoided in the future. My opinion is anti-traditional; the purpose of this article is to influence public health policy, and to save some of the limited resources and money for more important diseases like heart diseases, cancer, diabetes, AIDS, hepatitises, and tuberculosis (15) . Liting Song: conception of manuscript, drafting of manuscript, critical revision of manuscript, and final approval of manuscript. The author would like to recognize the contributions of the reviewers and editors of this manuscript for their corrections and editing, and Dr. Emanuel Goldman for correcting errors related to grammar and syntax of the final manuscript.	Approximately how many people died during the 1918-1919 influenza pandemic?	259	During the 1918-1919 influenza pandemic, between 21 and 25 million people died of influenza worldwide.	1,998

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