Code and data for paper Ruiyun Li, Sen Pei, Bin Chen, Yimeng Song, Tao Zhang, Wan Yang, and Jeffrey Shaman. Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2). (2020).
Code is programmed by Sen Pei (contact: sp3449@cumc.columbia.edu). Data are provided by Ruiyun Li, Bin Chen, Yimeng Song and Tao Zhang.
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 January 23, 2020 travel restrictions. Per person, these undocumented infections were 55% as contagious as documented infections ([46%-62%]) and were the source of infection for two-thirds of documented cases. These findings explain the rapid geographic spread of SARS-CoV2 and indicate containment of this virus will be particularly challenging.
The original paper came with matlab code. The same code was converted to a jupyter notebook.