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 the impact of COVID-19, but past analyses have 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 systems. Pearson correlation coefficients (CCs) were obtained for the most recent available pre-pandemic values against population-weighted age-standardized county excess death for each year from 2020 to 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). The strongest correlations were observed 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 under-65 population. Of 656 variables with |CC| > 0.30, 295 of 454 moderate-band and 200 of 202 strong-band variables belonged to demographic and socioeconomic super-clusters. Only 10% of health system variables reached |CC| > 0.30, compared to 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 leading variables unchanged, but the correlation magnitudes scaled with the weight given to large counties. Overall, these ecological analyses suggest stronger relationships between socioeconomic structure and demographics than between baseline health system structure and supply with excess mortality, especially during 2020–2021.