BACKGROUND: Health disparities, leading to worse health outcomes such as elevated COVID-19 mortality rates, are rooted in social and structural factors. These disparities notably impact individuals from lower socioeconomic backgrounds and more socially vulnerable areas. We analyzed the relationship between COVID-19 deaths and social vulnerability using the Minority Health Social Vulnerability Index (MHSVI). METHODS: COVID-19 death data in the U.S. was obtained from the Centers for Disease Control and Prevention (CDC) National Center for Health Statistics, where COVID-19 deaths were defined using the ICD-10 code U07.1. MHSVI composite scores were calculated for 3089 U.S. counties and categorized into social vulnerability quartiles, where values ranged from 0 (lowest vulnerability) to 1 (highest vulnerability). Negative binomial regression was employed to determine death rate ratios for each quartile within each theme. Finally, a multivariate negative binomial regression including all MHSVI sub-themes, excluding the overall index ranking, was used to assess the association between each theme and COVID-19 death rates independently. RESULTS: There were 1,134,272 COVID-19 deaths from January 1, 2020 through June 24, 2023. Adjusted rate ratios for COVID-19 deaths in the overall index ranking were 1.06 (95% CI 0.99-1.13), 1.14 (95% CI 1.06-1.22), and 1.41 (95% CI 1.31-1.52) for the second, third and fourth quartiles, respectively. Sub-themes of socioeconomic status (SES), household characteristics (HC), racial and ethnic minority status (REMS), housing type and transportation (HTT), and medical vulnerability (MV) revealed increasing death rates in higher vulnerability quartiles. The healthcare infrastructure and access (HIA) theme had decreasing death rate ratios of 0.74 (95% CI 0.71-0.78), 0.59 (95% CI 0.56-0.62), and 0.42 (95% CI 0.39-0.44) for the second, third, and fourth quartiles, respectively. Finally, the multivariate analysis showed that the HC, HTT, HIA, and MV themes were associated with COVID-19 deaths (P < 0.05). CONCLUSION: Counties that were identified as more socially vulnerable experienced higher death rates from COVID-19. These areas may need additional public health and social support during future pandemics.

INTRODUCTION: Health equity science examines underlying social determinants, or drivers, of health inequities by building an evidence base to guide action across programs, public health surveillance, policy, and communications efforts. A Social Vulnerability Index (SVI) was utilized during the COVID-19 response to identify areas where inequities exist and support communities with vaccination. We set out to assess COVID-19 vaccination coverage by two SVI themes, Racial and Ethnicity Minority Status and Housing Type and Transportation to examine disparities. METHODS: US county-level COVID-19 vaccine administration data among persons aged 5 years and older reported to the Centers for Disease Control and Prevention from December 14, 2020 to December 14, 2022, were analyzed. Counties were categorized 1) into tertiles (low, moderate, high) according to each SVI theme's level of vulnerability or 2) dichotomized by urban or rural classification. Primary series vaccination coverage per age group were assessed for SVI social factors by SVI theme tertiles or urbanicity. RESULTS: Older adults aged 65 years and older had the highest vaccination coverage across all vulnerability factors compared with children aged 5-17 years and adults aged 18-64 years. Overall, children and adults had higher vaccination coverage in counties of high vulnerability. Greater vaccination coverage differences were observed by urbanicity as rural counties had some of the lowest vaccination coverage for children and adults. CONCLUSION: COVID-19 vaccination efforts narrowed gaps in coverage for adults aged 65 years and older but larger vaccination coverage differences remained among younger populations. Moreover, greater disparities in coverage existed in rural counties. Health equity science approaches to analyses should extend beyond identifying differences by basic demographics such as race and ethnicity and include factors that provide context (housing, transportation, age, and geography) to assist with prioritization of vaccination efforts where true disparities in vaccination coverage exist.