  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.
