text: 252,226,1374716954276151296,14659319,Arash Badie-Modiri,"Check out our paper on contact tracing apps (i.e. #COVID19 exposure notification) where we study effects of degree distribution, homophily/heterophily of app users and failure (or people just not paying attention!) <LINK> (w/ @abbas_k_rizi @Faqeeh_ali_ @bolozna) For example, while heterophily is generally bad (since app users happen to interact with mostly non-app users, hence tracing apps are not used at all) too much homophily is also detrimental. There's a sweet spot for mixing of app users and non-app users. Also studied is the effect of targeting/convincing high degree nodes (socially highly active people) to use the app and to what extend this pushed the epidemic threshold back. Check it out on ArXiv: <LINK>",https://arxiv.org/abs/2103.12634,"Contact tracing via digital tracking applications installed on mobile phones is an important tool for controlling epidemic spreading. Its effectivity can be quantified by modifying the standard methodology for analyzing percolation and connectivity of contact networks. We apply this framework to networks with varying degree distributions, numbers of application users, and probabilities of quarantine failures. Further, we study structured populations with homophily and heterophily and the possibility of degree-targeted application distribution. Our results are based on a combination of explicit simulations and mean-field analysis. They indicate that there can be major differences in the epidemic size and epidemic probabilities which are equivalent in the normal SIR processes. Further, degree heterogeneity is seen to be especially important for the epidemic threshold but not as much for the epidemic size. The probability that tracing leads to quarantines is not as important as the application adoption rate. Finally, both strong homophily and especially heterophily with regard to application adoption can be detrimental. Overall, epidemic dynamics are very sensitive to all of the parameter values we tested out, which makes the problem of estimating the effect of digital contact tracing an inherently multidimensional problem. ","Epidemic Spreading and Digital Contact Tracing: Effects of Heterogeneous