Large-scale assessment of socioeconomic, demographic and health system structures with US county excess mortality, 2020-2024

Socioeconomic, demographic, and health system structures may have shaped COVID-19 pandemic impact across populations, but past analyses typically examined few factors. We systematically examined correlates of COVID-era excess mortality, considering 2,745 county-level variables of demography, race/ethnicity, income, insurance, education, employment, housing, and health system. Pearson correlation coefficients (CCs) were obtained for the most recent available pre-pandemic value against age-standardized county excess-death for each year during 2020-2024. Counties were population-weighted. Variables were grouped by meaning into 11 semantic super-clusters. Overall, 17.3% of variables reached at least a moderate correlation level (|CC| > 0.30) and 2.8% reached strong correlations (|CC| > 0.45). Strongest correlations were seen for college attainment (CC -0.54), uninsurance among adults 40-64 (+0.53), and high income (-0.53). At least moderate correlations were seen for 9.1% of variables in 2020 and 8.5% in 2021, but only 1.8%, 0%, and 1.3% in 2022, 2023, and 2024, respectively. Similar patterns of concentration of moderate correlations in the first two pandemic years appeared in both elderly and non-elderly populations. Of 472 variables with |CC| > 0.30, 362/395 moderate-band and 77/77 strong-band variables belonged to demography and socioeconomic super-clusters. Only 7% of health system variables reached |CC| > 0.30, versus 31% of socioeconomic and demographic variables. Using the most recent available value until 2023 or 2015, different population weighting, and Spearman correlations yielded similar results. Overall, these ecological analyses suggest strong relationships of socioeconomic structure and demographics rather than health-care resources/supply with excess mortality across US counties especially during 2020-2021.