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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.

Highlights • There was a non-linear association between discrimination and allostatic load. • The association between discrimination and allostatic load varied by education. • A U-shaped relationship emerged among those with lower education. • High discrimination had a buffering effect among those with higher education. • Associations were found for allostatic load and in system-specific analyses. Abstract Objective To examine the association between self-reported racial discrimination and allostatic load, and whether the association differs by socioeconomic position. Methods We recruited a purposive cross-section of midlife (ages 30–50) African American women residing in four San Francisco Bay area counties (n = 208). Racial discrimination was measured using the Experience of Discrimination scale. Allostatic load was measured as a composite of 15 biomarkers assessing cardiometabolic, neuroendocrine, and inflammatory activity. We calculated four composite measures of allostatic load and three system-specific measures of biological dysregulation. Multivariable regression was used to examine associations, while adjusting for relevant confounders. Results In the high education group, reporting low (b = −1.09, P =.02, 95% CI = −1.99, −0.18) and very high (b = −1.88, P =.003, 95% CI = −3.11, −0.65) discrimination was associated with lower allostatic load (reference=moderate). Among those with lower education, reporting low (b = 2.05, P =.008, 95% CI = 0.55,3.56) discrimination was associated with higher allostatic load. Similar but less consistent associations were found for poverty status. Associations were similar for cardiometabolic functioning, but not for neuroendocrine or inflammatory activity. Conclusions Racial discrimination may be an important predictor of cumulative physiologic dysregulation. Factors associated with educational attainment may mitigate this association for African American women and other groups experiencing chronic social stress. [ABSTRACT FROM AUTHOR]