Superspreading of SARS-CoV-2 in the USA

TL;DR

This paper introduces a method to estimate infectiousness variation in SARS-CoV-2, revealing significant superspreading where a small fraction of individuals cause most new cases in the US early pandemic.

Contribution

It provides a simple approach to quantify infectiousness heterogeneity and applies it to SARS-CoV-2, demonstrating the extent of superspreading in early US outbreaks.

Findings

Over 81% of cases caused by top 10% most infectious individuals

Infectiousness variation ratio $\sigma_eta/\mu_eta$ exceeds 3.2

Evidence of pervasive superspreading in early US SARS-CoV-2 spread

Abstract

A number of epidemics, including the SARS-CoV-1 epidemic of 2002-2004, have been known to exhibit superspreading, in which a small fraction of infected individuals is responsible for the majority of new infections. The existence of superspreading implies a fat-tailed distribution of infectiousness (new secondary infections caused per day) among different individuals. Here, we present a simple method to estimate the variation in infectiousness by examining the variation in early-time growth rates of new cases among different subpopulations. We use this method to estimate the mean and variance in the infectiousness, $\beta$, for SARS-CoV-2 transmission during the early stages of the pandemic within the United States. We find that $\sigma_\beta/\mu_\beta \gtrsim 3.2$, where $\mu_\beta$ is the mean infectiousness and $\sigma_\beta$ its standard deviation, which implies pervasive superspreading. This result allows us to estimate that in the early stages of the pandemic in the USA, over 81% of new cases were a result of the top 10% of most infectious individuals.