JUE Insight: Understanding spatial variation in COVID-19 across the United States

What factors explain spatial variation in the severity of COVID-19 across the United States? To answer this question, we analyze the correlates of COVID-19 cases and deaths across US counties. We document four sets of facts. First, effective density is an important and persistent determinant of COVID-19 severity. Second, counties with more nursing home residents, lower income, higher poverty rates, and a greater presence of African Americans and Hispanics are disproportionately impacted, and these effects show no sign of disappearing over time. Third, the effect of certain characteristics, such as the distance to major international airports and the share of elderly individuals, dies out over time. Fourth, Trump-leaning counties are less severely affected early on, but later suffer from a large severity penalty.

Automated summary

By analyzing the factors related to COVID-19 cases and deaths in US counties, this study reveals several findings. Firstly, effective density is an important and persistent determinant of COVID-19 severity. Secondly, counties with more nursing home residents, lower income, higher poverty rates, and a greater presence of African Americans and Hispanics are disproportionately impacted, and these effects do not disappear over time. Thirdly, the effects of certain characteristics, such as distance to major international airports and the share of elderly individuals, diminish over time. Lastly, Trump-leaning counties are initially less severely affected, but later experience a significant penalty in severity.