Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2)

TLDR

Estimation of the prevalence and contagiousness of undocumented SARS‑CoV‑2 infections is critical for understanding the overall prevalence and pandemic potential of this disease. The study aims to infer key epidemiological characteristics of SARS‑CoV‑2, such as the proportion of undocumented infections and their contagiousness. Using reported case data, mobility information, a networked dynamic metapopulation model, and Bayesian inference, the authors estimate these characteristics. They estimate that 86 % of infections were undocumented, that undocumented cases transmit at about 55 % the rate of documented cases, yet due to their numbers they account for 79 % of documented infections, explaining the rapid spread and the difficulty of containment.

Abstract

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.