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The COVID-19 pandemic has emerged as a global public health crisis. To makedecisions about mitigation strategies and to understand the disease dynamics,policy makers and epidemiologists must know how the disease is spreading intheir communities. We analyze confirmed infections and deaths over multiplegeographic scales to show that COVID-19's impact is highly unequal: manysubregions have nearly zero infections, and others are hot spots. We attributethe effect to a Reed-Hughes-like mechanism in which disease arrives atdifferent times and grows exponentially. Hot spots, however, appear to growfaster than neighboring subregions and dominate spatially aggregatedstatistics, thereby amplifying growth rates. The staggered spread of COVID-19can also make aggregated growth rates appear higher even when subregions growat the same rate. Public policy, economic analysis and epidemic modeling needto account for potential distortions introduced by spatial aggregation.

Unequal Impact and Spatial Aggregation Distort COVID-19 Growth Rates