Li, Ruiyun Pei, Sen Chen, Bin Song, Yimeng Zhang, Tao Yang, Wan Shaman, Jeffrey text monographic eng

print

Estimation of the prevalence and contagiousness of undocumented novel coronavirus [severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2)] infections is critical for understanding the overall prevalence and pandemic potential of this disease. Here, we use observations of reported infection within China, in conjunction with mobility data, a networked dynamic metapopulation model, and Bayesian inference, to infer critical epidemiological characteristics associated with SARS-CoV-2, including the fraction of undocumented infections and their contagiousness. We estimate that 86% of all infections were undocumented [95% credible interval (CI): 82-90%] before the 23 January 2020 travel restrictions. The transmission rate of undocumented infections per person was 55% the transmission rate of documented infections (95% CI: 46-62%), yet, because of their greater numbers, undocumented infections were the source of 79% of the documented cases. These findings explain the rapid geographic spread of SARS-CoV-2 and indicate that containment of this virus will be particularly challenging. Ruiyun Li [and six others] In: Science. 2020 vol.368 (6490) page: 489–493. Published online 2020 Mar 16. doi: 10.1126/science.abb3221 Bayes Theorem Betacoronavirus Coronavirus Infections diagnosis Coronavirus Infections transmission Epidemiological Monitoring Travel COVID-19 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7164387/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7164387/ 201123 20201123132702.0 D0001C000066