A national growth mixture modeling analysis of county-level COVID-19 incidence rate trajectories and health inequities during three successive pandemic waves in 2020.

ABSTRACT: We applied Growth Mixture Modeling (GMM) to characterize county-level COVID-19 incidence rate (IR) trajectories across three distinct waves in the United States from March 15 to November 2, 2020. GMM enabled the identification of latent subpopulations with shared temporal patterns of disease spread, offering a flexible analytic framework for uncovering both known and evolving disparities. Across the three periods, up to five trajectory groups were identified, revealing substantial geographic and temporal heterogeneity. To support interpretation and reduce multiple comparisons, we developed and validated a 17-item Social Determinants of Health (SDOH) index representing county-level economic and resource access factors. Higher-incidence rate trajectories consistently aligned with lower SDOH

SUBMITTER: Dukes K 

PROVIDER: S-EPMC12638980 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature