Before revision:  We analyze US county-level data about confirmed COVID-19 infections and deaths  to show that its impact is heterogeneous. A small fraction of counties represent the majority of all infectionsand deaths. These hot spotsare correlated with populous areas where the disease arrives earlier and grows faster. When county-level data is aggregated to create state-level and national statistics, these hot spots systematically bias the growth rates.
After revision:  We analyze US county-level data about confirmed COVID-19 infections and deaths to show that COVID-19's impact is highly unequal: many subregions have nearly zero infections, and others are hot spots. We attribute the effect to a Reed-Hughes-like mechanism in which disease arrives at different times and grows exponentially. Hot spots, however, appear to grow faster than neighboring subregions and dominate spatially aggregated statistics, thereby amplifying growth rates.