Whites’ County-Level Racial Bias, COVID-19 Rates, and Racial Inequities in the United States

Marilyn D. Thomas, Eli K. Michaels, Sean Darling-Hammond, Thu T. Nguyen, M. Maria Glymour and Eric Vittinghoff
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Marilyn D. Thomas: Department of Epidemiology and Biostatistics, School of Medicine, University of California, 550 16th St 2nd floor, San Francisco, CA 94158, USA
Eli K. Michaels: Division of Epidemiology, School of Public Health, University of California, 2121 Berkeley Way, Room 5302, Berkeley, CA 94720, USA
Sean Darling-Hammond: Goldman School of Public Policy, University of California, 2607 Hearst Ave, Berkeley, CA 94720, USA
Thu T. Nguyen: Department of Family and Community Medicine, School of Medicine, University of California, 995 Potrero Ave, San Francisco, CA 94110, USA
M. Maria Glymour: Department of Epidemiology and Biostatistics, School of Medicine, University of California, 550 16th St 2nd floor, San Francisco, CA 94158, USA
Eric Vittinghoff: Department of Epidemiology and Biostatistics, School of Medicine, University of California, 550 16th St 2nd floor, San Francisco, CA 94158, USA

IJERPH, 2020, vol. 17, issue 22, 1-19

Abstract: Mounting evidence reveals considerable racial inequities in coronavirus disease 2019 (COVID-19) outcomes in the United States (US). Area-level racial bias has been associated with multiple adverse health outcomes, but its association with COVID-19 is yet unexplored. Combining county-level data from Project Implicit on implicit and explicit anti-Black bias among non-Hispanic Whites, Johns Hopkins Coronavirus Resource Center, and The New York Times , we used adjusted linear regressions to estimate overall COVID-19 incidence and mortality rates through 01 July 2020, Black and White incidence rates through 28 May 2020, and Black–White incidence rate gaps on average area-level implicit and explicit racial bias. Across 2994 counties, the average COVID-19 mortality rate (standard deviation) was 1.7/10,000 people (3.3) and average cumulative COVID-19 incidence rate was 52.1/10,000 (77.2). Higher racial bias was associated with higher overall mortality rates (per 1 standard deviation higher implicit bias b = 0.65/10,000 (95% confidence interval: 0.39, 0.91); explicit bias b = 0.49/10,000 (0.27, 0.70)) and higher overall incidence (implicit bias b = 8.42/10,000 (4.64, 12.20); explicit bias b = 8.83/10,000 (5.32, 12.35)). In 957 counties with race-specific data, higher racial bias predicted higher White and Black incidence rates, and larger Black–White incidence rate gaps. Anti-Black bias among Whites predicts worse COVID-19 outcomes and greater inequities. Area-level interventions may ameliorate health inequities.

Keywords: COVID-19; health inequities; racism and discrimination; social determinants of health (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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