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The Magnitude of Black/Hispanic Disparity in COVID-19 Mortality Across United States Counties During the First Waves of the COVID-19 Pandemic.

ABSTRACT: Objectives: To quantify the Black/Hispanic disparity in COVID-19 mortality in the United States (US). Methods: COVID-19 deaths in all US counties nationwide were analyzed to estimate COVID-19 mortality rate ratios by county-level proportions of Black/Hispanic residents, using mixed-effects Poisson regression. Excess COVID-19 mortality counts, relative to predicted under a counterfactual scenario of no racial/ethnic disparity gradient, were estimated. Results: County-level COVID-19 mortality rates increased monotonically with county-level proportions of Black and Hispanic residents, up to 5.4-fold (≥43% Black) and 11.6-fold (≥55% Hispanic) higher compared to counties with <5% Black and <15% Hispanic residents, respectively, controlling for county-level poverty, age, and urbanization level. Had this disparity gradient not existed, the US COVID-19 death count would have been 92.1% lower (177,672 fewer deaths), making the rate comparable to other high-income countries with substantially lower COVID-19 death counts. Conclusion: During the first 8 months of the SARS-CoV-2 pandemic, the US experienced the highest number of COVID-19 deaths. This COVID-19 mortality burden is strongly associated with county-level racial/ethnic diversity, explaining most US COVID-19 deaths.

SUBMITTER: Im C

PROVIDER: S-EPMC8493931 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundUnderstanding the current burden of coronavirus disease 2019 (COVID-19) deaths in vulnerable populations will help inform efforts by policymakers to address disparities in COVID-19 outcomes.ObjectiveThe objective of this study was to examine the association between COVID-19 deaths and the county-level proportions of non-Hispanic Black and Hispanic residents.Research design and methodsA retrospective study using COVID-19 mortality data from USA Facts linked to data from the US Census Bureau, the Health Resources & Services Administration Area Health Resources file, and the US Census Bureau. Negative binomial regression was used to estimate the association between the total county COVID-19 deaths during consecutive 30-day intervals and the proportion of non-Hispanic Blacks and Hispanic residents after adjusting for resident demographics, comorbidity burden, rurality, social determinants of health, and health care resources.ResultsIn April, counties (n=179) with >40% Blacks had 6-fold higher death rates than counties (n=1521) with <2% Blacks [incident rate ratio (IRR)=6.58, 95% confidence interval (CI): 3.29-13.2, P<0.001]. These counties had higher death rates until October, but were no different than referent counties in November. In April, death rates in counties with >40% Hispanic residents were similar to death rates in counties with <2% Hispanic residents. Death rates in these counties peaked in August (IRR=3.14, 95% CI: 1.69-5.82, P<0.001) but were also no different than referent counties in November. These effects were robust after adjusting for county-level characteristics. Before August, death rates differed little by insurance status, but since then, counties with >15% uninsurance rates had up to 2-fold higher mortality rates (IRR=1.97, 95% CI: 1.19-3.27, P<0.001) than counties with <5% uninsurance rates.ConclusionCounties with high concentrations of non-Hispanic Blacks were disproportionately affected by COVID-19 throughout most of the pandemic, but other social determinants of health such as health insurance are now playing a more prominent role than race and ethnicity.

Project description:BackgroundBased on individual-level studies, previous literature suggested that conservatives and liberals in the United States had different perceptions and behaviors when facing the COVID-19 threat. From a state-level perspective, this study further explored the impact of personal political ideology disparity on COVID-19 transmission before and after the emergence of Omicron.MethodsA new index was established, which depended on the daily cumulative number of confirmed cases in each state and the corresponding population size. Then, by using the 2020 United States presidential election results, the values of the built index were further divided into two groups concerning the political party affiliation of the winner in each state. In addition, each group was further separated into two parts, corresponding to the time before and after Omicron predominated. Three methods, i.e., functional principal component analysis, functional analysis of variance, and function-on-scalar linear regression, were implemented to statistically analyze and quantify the impact.ResultsFindings reveal that the disparity of personal political ideology has caused a significant discrepancy in the COVID-19 crisis in the United States. Specifically, the findings show that at the very early stage before the emergence of Omicron, Democratic-leaning states suffered from a much greater severity of the COVID-19 threat but, after July 2020, the severity of COVID-19 transmission in Republican-leaning states was much higher than that in Democratic-leaning states. Situations were reversed when the Omicron predominated. Most of the time, states with Democrat preferences were more vulnerable to the threat of COVID-19 than those with Republican preferences, even though the differences decreased over time.ConclusionsThe individual-level disparity of political ideology has impacted the nationwide COVID-19 transmission and such findings are meaningful for the government and policymakers when taking action against the COVID-19 crisis in the United States.

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The Magnitude of Black/Hispanic Disparity in COVID-19 Mortality Across United States Counties During the First Waves of the COVID-19 Pandemic.

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