| dc.contributor.author | Li R. MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London W2 1PG, UK | |
| dc.date.accessioned | 2020-03-18T16:12:07Z | |
| dc.date.available | 2020-03-18T16:12:07Z | |
| dc.date.issued | 2020-03-16 | |
| dc.identifier.uri | https://doi.org/10.1126/science.abb3221 | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.12663/444 | |
| dc.description.abstract | Estimation of the prevalence and contagiousness of undocumented novel coronavirus (SARS-CoV2) 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-CoV2, including the fraction of undocumented infections and their contagiousness. We estimate 86% of all infections were undocumented (95% CI: [82%-90%]) prior to 23 January 2020 travel restrictions. Per person, the transmission rate of undocumented infections was 55% of documented infections ([46%-62%]), yet, due to their greater numbers, undocumented infections were the infection source for 79% of documented cases. These findings explain the rapid geographic spread of SARS-CoV2 and indicate containment of this virus will be particularly challenging. | en_US |
| dc.title | Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2) | en_US |
| eihealth.country | Others | en_US |
| eihealth.category | Virus: natural history, transmission and diagnostics | en_US |
| eihealth.type | Published Article | en_US |
