Black–White Risk Differentials in COVID-19 (SARS-COV2) Transmission, Mortality and Case Fatality in the United States: Translational Epidemiologic Perspective and Challenges

Abstract

Background: Social and health inequities predispose vulnerable populations to adverse morbidity and mortality outcomes of epidemics and pandemics. While racial disparities in cumulative incidence (CmI) and mortality from the influenza pandemics of 1918 and 2009 implicated Blacks with survival disadvantage relative to Whites in the United States, COVID-19 currently indicates comparable disparities. We aimed to: (a) assess COVID-19 CmI by race, (b) determine the Black–White case fatality (CF) and risk differentials, and (c) apply explanatory model for mortality risk differentials. Methods: COVID-19 data on confirmed cases and deaths by selective states health departments were assessed using a cross-sectional ecologic design. Chi-square was used for CF independence, while binomial regression model for the Black–White risk differentials. Results: The COVID-19 mortality CmI indicated Blacks/AA with 34% of the total mortality in the United States, albeit their 13% population size. The COVID-19 CF was higher among Blacks/AA relative to Whites; Maryland, (2.7% vs. 2.5%), Wisconsin (7.4% vs. 4.8%), Illinois (4.8% vs. 4.2%), Chicago (5.9% vs. 3.2%), Detroit (Michigan), 7.2% and St. John the Baptist Parish (Louisiana), 7.9%. Blacks/AA compared to Whites in Michigan were 15% more likely to die, CmI risk ratio (CmIRR) = 1.15, 95% CI, 1.01–1.32. Blacks/AA relative to Whites in Illinois were 13% more likely to die, CmIRR = 1.13, 95% CI, 0.93–1.39, while Blacks/AA compared to Whites in Wisconsin were 51% more likely to die, CmIRR = 1.51, 95% CI, 1.10–2.10. In Chicago, Blacks/AA were more than twice as likely to die, CmIRR = 2.24, 95% CI, 1.36–3.88. Conclusion: Substantial racial/ethnic disparities are observed in COVID-19 CF and mortality with Blacks/AA disproportionately affected across the United States.

Biological Factors Linking ApoE ε4 Variant and Severe COVID-19

“…If the ApoE ε4 allele indeed influences COVID-19 severity, this may explain the prevalence of severe disease amongst certain ethnicities, as in one study the allele frequency was 29.5% for AA versus 12.1% for the Caucasian group [9]. Furthermore, up to mid-April 2020, 34% of deaths from COVID-19 in the USA occurred amongst AAs, despite the population representing only 13% of all Americans [10]. In conclusion, ApoE ε4 may have multifaceted effects in COVID-19 which may also be reflected in ethnicity.…”

Modeling the incidence and death rates of COVID-19 pandemic in different regions of the world

“…However, for many other authors, the epidemic has the potential to have a major impact on these populations, considering poverty, the greater agglomeration, as well as the poor conditions of health services (Lumu 2020;Ongole et al 2020;Osseni 2020). Countries in North America region presents the larger MRC, perhaps partly explained by the high population density and differences in age and racial structures of countries in that region with the greatest weight in Mexico and United States (Holmes et al 2020;Mendez-Dominguez et al 2020) while the CFR show more variability among the 11 regions with larger values for the countries in North Africa region, certainly largely due to poor health service structures in the countries of that region, with little capacity to deal with good response to critically ill patients, due to the lack of ICU beds and trained medical personnel (Ohia et al, 2020). Table 1 presents summary statistics (means, standard-deviations, minimum and maximum for the IR, MRC and CFR for each region (Asia Middle East; Central America; Central Asia; Caribbean; East Asia; Europe; North Africa; North America; Oceania; South America; Sub Saharan Africa).…”

A higher ratio of green spaces means a lower racial disparity in severe acute respiratory syndrome coronavirus 2 infection rates: A nationwide study of the United States

“…As of July 10, 2020, there were a total of 1,425,461 cases of SARS-CoV-2 infection in the 135 most urbanized counties in the United States, which accounted for 47% of the total cases of infection (3,038,325) in the United States (Figure 1). The 135 most urbanized counties were selected because they contain or overlap with 314 large cities with a population ≥ 100,000 in 2019 (see details in Methods).…”