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 impact, but past analyses 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 population-weighted age-standardized county excess-death for each year during 2020–2024. Variables were grouped by meaning into 11 semantic super-clusters. Overall, 24.1% of variables reached at least a moderate correlation level (|CC| > 0.30) and 7.4% reached strong correlations (| CC| > 0.45). Strongest correlations were seen for poverty share (CC +0.64), college attainment (−0.62), and high income (−0.61). At least moderate correlations were seen for 11.4% of variables in 2020 and 14.8% in 2021, but only 3.3%, 1.3%, and 4.1% in 2022, 2023, and 2024, respectively. The concentration in 2020–2021 was sharpest in the non-elderly population. Of 656 variables with |CC| > 0.30, 295/454 moderate-band and 200/202 strong-band variables belonged to demography and socioeconomic super-clusters. Only 10% of health system variables reached | CC| > 0.30, versus 42% of socioeconomic and demographic variables. Using the most recent available value until 2023 or 2015, different population weighting, and Spearman correlations left the direction and the leading variables unchanged, but the correlation magnitudes scale with the weight given to large counties. Overall, these ecological analyses suggest stronger relationships of socioeconomic structure and demographics than of baseline health-system structure and supply with excess mortality, especially during 2020–2021.