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1,880 | 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? | {
"answer_start": [
1779
],
"text": [
"019-nCoV at 2.56 (95% CI"
]
} | false |
1,881 | 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? | {
"answer_start": [
1865
],
"text": [
" to have occurred during the first ha"
]
} | false |
1,882 | 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? | {
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1,884 | 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? | {
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"text": [
"ymptoms including fever, cough, and sh"
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} | false |
1,886 | 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? | {
"answer_start": [
2266
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"text": [
"sed"
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1,889 | 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? | {
"answer_start": [
2405
],
"text": [
"k had resulted in 2066 (618 of them are in Wuhan) confirmed cases and 56 (45 of them were in Wuhan) deaths in "
]
} | false |
1,891 | 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? | {
"answer_start": [
2574
],
"text": [
" were reported in Thailand, Japan, Republic of Korea, Hong Kong, Taiwan, Australia, and"
]
} | false |
1,892 | 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? | {
"answer_start": [
2927
],
"text": [
"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"
]
} | false |
1,893 | 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? | {
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1,894 | 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? | {
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1,895 | 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? | {
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1,907 | 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? | {
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3,692 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What study is reported in this report? | {
"answer_start": [
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"text": [
"bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes."
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3,693 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | How does the genome of 2019-vCOV compare with SARS like viruses and SARS-COV? | {
"answer_start": [
855
],
"text": [
"Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses."
]
} | false |
3,694 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | How different is it from SARS-related viruses? | {
"answer_start": [
1157
],
"text": [
"the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. "
]
} | false |
3,695 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What novel features does the genome have? | {
"answer_start": [
1314
],
"text": [
" its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands."
]
} | false |
3,696 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What is important for understanding the origin and evolution of this novel lineage B betacoronavirus. | {
"answer_start": [
1503
],
"text": [
"Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus"
]
} | false |
3,697 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What are Coronaviruses? | {
"answer_start": [
1935
],
"text": [
"Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales."
]
} | false |
3,698 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What are four generas? | {
"answer_start": [
2139
],
"text": [
"Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) "
]
} | false |
3,699 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What do evolutionary analyses show? | {
"answer_start": [
2279
],
"text": [
" that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs."
]
} | false |
3,700 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What are the examples that have emerged as human pathogens? | {
"answer_start": [
2544
],
"text": [
"severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012"
]
} | false |
3,701 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | Where did these viruses originate before crossing the barrier to infect humans? | {
"answer_start": [
2868
],
"text": [
"these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] "
]
} | false |
3,702 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What COVs were known to infect humans before December 2019? | {
"answer_start": [
3165
],
"text": [
"6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [ "
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} | false |
3,703 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What do HCoV-OC43 and HCoV-HKU1 cause? | {
"answer_start": [
3306
],
"text": [
"self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly "
]
} | false |
3,704 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What is the contrast with SARS-COV and MERS=COV? | {
"answer_start": [
3483
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"text": [
" SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively "
]
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3,705 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What was the authors' recent report on? | {
"answer_start": [
4684
],
"text": [
"a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan "
]
} | false |
3,706 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What is analyzed in this study? | {
"answer_start": [
4817
],
"text": [
"a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies."
]
} | false |
3,707 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What genome sequence was available for this study? | {
"answer_start": [
5038
],
"text": [
"2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262)"
]
} | false |
3,708 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What strains were included in this study? | {
"answer_start": [
5277
],
"text": [
"strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup."
]
} | false |
3,709 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | How was the Phylogenetic construction done? | {
"answer_start": [
5442
],
"text": [
" by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees"
]
} | false |
3,710 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | How were the evolutionary distances computed? | {
"answer_start": [
5918
],
"text": [
"using the Poisson correction method and were in the units of the number of amino acid substitutions per site ["
]
} | false |
3,711 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | How was the structural analysis of orf8 done? | {
"answer_start": [
6314
],
"text": [
"using PSI-blast-based secondary structure PREDiction (PSIPRED) "
]
} | false |
3,712 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What was done for the prediction of protein secondary structures? | {
"answer_start": [
6478
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" initial amino acid sequences were input and analysed using neural networking and its own algorithm. "
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3,713 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What is the RNA of the 2019-nCOV? | {
"answer_start": [
7519
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"text": [
"29891 nucleotides in size, encoding 9860 amino acids"
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3,714 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What was the G+C content? | {
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3,715 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | How are 2019-nCOV and SARS-COV similar? | {
"answer_start": [
7629
],
"text": [
"There are no remarkable differences between the orfs and nsps"
]
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3,716 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | Where is the major distinction? | {
"answer_start": [
7794
],
"text": [
" in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots."
]
} | false |
3,717 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What do the S1 and S2 subunits of spike glycoprotein contain? | {
"answer_start": [
7977
],
"text": [
"The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP)."
]
} | false |
3,718 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What are the chacateristics of the S2 subunit? | {
"answer_start": [
8256
],
"text": [
"S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV "
]
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3,719 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What would be the benefit of the identity of the S2 unit? | {
"answer_start": [
8425
],
"text": [
" the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials "
]
} | false |
3,720 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | How do the S1 subunits compare with that of SARS-likeCOV and human SARS-COV? | {
"answer_start": [
8590
],
"text": [
"Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved ("
]
} | false |
3,721 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | Where are the amino acid differences? | {
"answer_start": [
8820
],
"text": [
"Most of the amino acid differences of RBD are located in the external subdomain,"
]
} | false |
3,722 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What is responsible for the interaction with host receptor? | {
"answer_start": [
8876
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" the external subdomain,"
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3,723 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | what will the investigation of external subdomain reveal? | {
"answer_start": [
9058
],
"text": [
"its receptor usage, interspecies transmission and pathogenesis."
]
} | false |
3,724 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | How do most bat SARSr-COV differ from 2019-nCOV and human SARS-COV? | {
"answer_start": [
9170
],
"text": [
"bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV"
]
} | false |
3,726 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | Which strains do not have such deletions? | {
"answer_start": [
9312
],
"text": [
"Yunnan strains such as the WIV1"
]
} | false |
3,727 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What is the consequence of lack of deletions in Yunnan strains? | {
"answer_start": [
9370
],
"text": [
"can use human ACE2 as a cellular entry receptor. "
]
} | false |
3,728 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | Being closest to 2019-nCoV, which species do the two bat SARS-related coronavirus ZXC21 and ZC45 infect? | {
"answer_start": [
9531
],
"text": [
"can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. "
]
} | false |
3,729 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What would lessen the likelihood of jumping the barrier? | {
"answer_start": [
9747
],
"text": [
"The two retained deletion sites in the Spike genes of ZXC21 and ZC45"
]
} | false |
3,730 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What do the results indicate? | {
"answer_start": [
10950
],
"text": [
" that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis."
]
} | false |
3,731 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What is orf8? | {
"answer_start": [
11292
],
"text": [
"an accessory protein found in the Betacoronavirus lineage B coronaviruses"
]
} | false |
3,732 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What orf8 length do Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain? | {
"answer_start": [
11480
],
"text": [
"fulllength orf8"
]
} | false |
3,733 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | From where have the original SARS-CON orf8 been acquired? | {
"answer_start": [
11772
],
"text": [
"two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) "
]
} | false |
3,734 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What does the orf8 derived from 2019-nCOV belong to? | {
"answer_start": [
12654
],
"text": [
"the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. "
]
} | false |
3,735 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What is the relation between the new2019-nCOV and the conserved orf8? | {
"answer_start": [
12762
],
"text": [
"the new 2019-nCoV orf8 is distant from the conserved orf8 "
]
} | false |
3,736 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | orf8 was shown to do what? | {
"answer_start": [
12853
],
"text": [
"to trigger intracellular stress pathways and activates NLRP3 inflammasomes"
]
} | false |
3,737 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What high possibility does the novel orf8 have? | {
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3,738 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What is the summary of this report? | {
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"2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV."
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4,221 | 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? | {
"answer_start": [
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"Wuhan, Hubei Province, China"
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529 | 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? | {
"answer_start": [
847
],
"text": [
"Global Initiative on Sharing All Influenza Data (GISAID) (https://www.gisaid.org/)"
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} | false |
531 | 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? | {
"answer_start": [
1501
],
"text": [
"E and RdRp genes"
]
} | false |
266 | 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? | {
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"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)"
]
} | false |
267 | 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? | {
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"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"
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2,185 | 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? | {
"answer_start": [
3118
],
"text": [
"limited information available regarding incubation time, transmissibility, and virus origin"
]
} | false |
2,186 | 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?
| {
"answer_start": [
4564
],
"text": [
"Washington"
]
} | false |
2,187 | 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? | {
"answer_start": [
4421
],
"text": [
"January 15, 2020"
]
} | false |
2,188 | 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? | {
"answer_start": [
4723
],
"text": [
"January 24, 2020"
]
} | false |
2,189 | 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? | {
"answer_start": [
4667
],
"text": [
"Chicago"
]
} | false |
2,190 | 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? | {
"answer_start": [
4929
],
"text": [
"January 30, 2020"
]
} | false |
2,191 | 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? | {
"answer_start": [
4929
],
"text": [
"January 30, 2020"
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} | false |
2,192 | 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? | {
"answer_start": [
5172
],
"text": [
"January 31, 2020,"
]
} | false |
2,193 | 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? | {
"answer_start": [
6790
],
"text": [
"Fever and cough "
]
} | false |
2,194 | 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? | {
"answer_start": [
7166
],
"text": [
"patients with underlying medical conditions and the elderly"
]
} | false |
2,195 | 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? | {
"answer_start": [
7166
],
"text": [
"patients with underlying medical conditions and the elderly"
]
} | false |
2,196 | 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? | {
"answer_start": [
7356
],
"text": [
"between 2 and 14 days"
]
} | false |
2,197 | 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? | {
"answer_start": [
11444
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2,198 | 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? | {
"answer_start": [
14067
],
"text": [
"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"
]
} | false |
1,909 | 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? | {
"answer_start": [
369
],
"text": [
"168 million people across 50 countries"
]
} | false |
1,910 | 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? | {
"answer_start": [
964
],
"text": [
"those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. "
]
} | false |
1,911 | 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? | {
"answer_start": [
1096
],
"text": [
"Poor governance, public distrust, and political violence "
]
} | false |
1,912 | 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? | {
"answer_start": [
1209
],
"text": [
"Populations affected by humanitarian crises "
]
} | false |
1,913 | 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? | {
"answer_start": [
1344
],
"text": [
"due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization"
]
} | false |
1,914 | 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? | {
"answer_start": [
1472
],
"text": [
"Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. "
]
} | false |
1,915 | 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? | {
"answer_start": [
2255
],
"text": [
" limited public health, laboratory, and primary care services "
]
} | false |
1,916 | 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? | {
"answer_start": [
2349
],
"text": [
"Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain "
]
} | false |
1,917 | 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? | {
"answer_start": [
2580
],
"text": [
" Frequent displacement and limited contact information "
]
} | false |
1,918 | 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? | {
"answer_start": [
2725
],
"text": [
"overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. "
]
} | false |
1,919 | 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? | {
"answer_start": [
2847
],
"text": [
"increased vulnerabilities, humanitarian crises"
]
} | false |
1,920 | 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? | {
"answer_start": [
3037
],
"text": [
"to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases."
]
} | false |
1,921 | 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? | {
"answer_start": [
3371
],
"text": [
" Respiratory hygiene i"
]
} | false |
1,922 | 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? | {
"answer_start": [
3558
],
"text": [
"hand hygiene, safe cough practice, and social distancing ["
]
} | false |
1,923 | 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? | {
"answer_start": [
3668
],
"text": [
" the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30%"
]
} | false |
1,924 | 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? | {
"answer_start": [
3888
],
"text": [
"the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. "
]
} | false |
1,925 | 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? | {
"answer_start": [
3994
],
"text": [
"Widespread introduction of alcohol-based hand rubs "
]
} | false |
1,926 | 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? | {
"answer_start": [
4150
],
"text": [
"The Sphere Handbook, a collection of rights-based guidelines for humanitarian response"
]
} | false |
1,927 | 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? | {
"answer_start": [
4398
],
"text": [
" reducing both bacterial and viral pathogen transmission,"
]
} | false |
1,928 | 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? | {
"answer_start": [
4497
],
"text": [
"evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines"
]
} | false |
1,929 | 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? | {
"answer_start": [
4657
],
"text": [
"latrines in crisis settings are often shared and distant from residential shelters,"
]
} | false |
1,930 | 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? | {
"answer_start": [
4858
],
"text": [
" for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission."
]
} | false |
1,931 | 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? | {
"answer_start": [
5265
],
"text": [
"Crisis-affected community engagement is integral in pandemic planning,"
]
} | false |
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