Objectives: To quantify the contribution variation in socioeconomic status in predicting the distribution of COVID-19 cases and deaths.
Methods: Analyses used incidence data on daily COVID + case counts from all counties from the initial wave of infections, merged with data from the U.S. census data to measure county-level SES and confounders. Multivariable analyses relied on survival analyses and Poisson regression to examine timing of county-level index cases and of COVID-19 incidence and mortality in infected counties to examine the spread and severity of COVID-19 while adjusting for adjusted for Black race, Hispanic ethnicity, age, gender, and urbanicity. Effect moderation by social distancing parameters was examined.
Results: Results indicate that higher SES was associated with earlier incidence of index cases, but that as social distancing took place inequalities in SES inverted so that growth in incidence was slower in higher SES counties, where case-fatality rates were lower.
Conclusions: This study is the first to date to show what happens when an opportunistic disease that could affect anyone meets the American system of inequality and is powerfully shaped by it.
Keywords: COVID-19; Fundamental cause theory; Socioeconomic inequalities and health.
Copyright © 2020. Published by Elsevier Ltd.