Association Between County-Level Racial and Ethnic Characteristics and COVID-19 Cases and Deaths in the USA
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J Gen Intern Med DOI: 10.1007/s11606-020-06083-8 © Society of General Internal Medicine 2020
Coronavirus disease 2019 (COVID-19) has resulted in over 1.5 million infections and 100,000 deaths in the USA. Early reports indicated that communities with high proportions of racial and ethnic minorities may be disproportionately affected. However, existing evidence is limited to studies that examined simple correlations without adjustments for potential confounders1 or compared counties in a single state (Massachusetts).2 Another recent study sought to answer this question by using national county-level data, but compared counties with disproportionately high numbers of Black residents—which are predominantly (91%) located in the South—versus counties with a lower proportion of Black residents across states. Therefore, the study effectively compared the South versus other regions of the USA.3 More importantly, states vary substantially in their responses to the COVID-19 pandemic; therefore, not accounting for state characteristics may lead to biased estimates of the relationship between the proportion of Black residents and the impact of COVID-19 outbreaks.
Adjustment variables included county-level percent female, 65+ years, uninsured, and mean household size (2018 ACS); urbanicity (National Center for Health Statistics 2013 Urban-Rural Classification Scheme); air quality and health outcome quartile (a composite measure of the length and quality of life, comparing counties within states4) (2020 Robert Wood Johnson Foundation County Health Rankings and Roadmaps); total physicians and hospital beds per capita (2018–2019 Area Health Resources Files from the Health Resources and Services Administration); the existence of a stay-at-home policy (New York Times database5); and the number of days from the first county-reported COVID-19 case (JHU CSSE). We adjusted for state fixed effects, which control for unobserved factors that vary by state (effectively comparing counties within states). We first created maps illustrating the geographic distribution of race/ethnicity and COVID-19 cases and deaths. We then examined adjusted associations between the proportion of racial and ethnic minorities and COVID-19 cases and deaths, using multivariable negative binomial regression models. To account for multiple comparisons, we considered P < 0.01 to be statistically significant. All analyses were conducted using Stata/SE 16.0. This study was exempted from review by the UCLA Institutional Review Board.
METHODS
RESULTS
The exposure variables included county-level percent Black, percent Hispanic, median household income, percent poverty, and percent unemployment (the 2018 American Community Survey [ACS] and the February 2020 Bureau of Labor Statistics unemployment report). The outcome variables included county-level COVID-19 cases and deaths per 100,000 population (Center for Systems Science and Engineering [CSSE] at Johns Hopkins University [JHU]). We limited our analysis to the 50 states and the District of Columbia from January 22
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