Mapping Long COVID: Spatial and Social Inequities Across the United States

BackgroundLong COVID affects a substantial portion of the U.S. population, yet its spatiotemporal distribution remains poorly characterized. The emergence of the Omicron variant and persistent sociodemographic disparities may contribute to regional variation in long COVID risk. Understanding the patterns of long COVID is essential to implementing targeted and equitable public health interventions. MethodsThis retrospective study utilized data from the National COVID Cohort Collaborative (N3C), covering 5,652,474 COVID-19 cases and 41,694 long COVID cases across 1,063 U.S. counties from 2021 to 2024. Temporal patterns of long COVID were analyzed before and after the Omicron variants emergence, and spatial patterns were assessed using Morans I and Getis statistics. Bayesian spatial random effect models were employed to evaluate the associations between long COVID incidence and sociodemographic factors such as economic vulnerability, healthcare access, and mobility. FindingsQuarterly long COVID incidence ranged from 0.015% to 14.29%. Before the emergence of the Omicron variant, incidence was 204 cases per 10,000 COVID-19 cases, compared with 248 cases per 10,000 COVID-19 cases after Omicron emergence (p < 0.001). After Omicrons emergence, 48.8% [328 of 673] of counties showed significant spatial correlation (p < 0.05), up from 43.5% [293 of 673] prior. High-risk areas became more concentrated in inland regions, while low-risk areas clustered along the East Coast. Long COVID incidence was significantly associated with economic vulnerability, limited healthcare access, and mobility constraints, with these sociodemographic disparities consistently driving its spatial disparities over time. InterpretationThese findings underscore the need to address spatial and social inequities in long COVID risk. Targeted public health interventions, particularly in economically and geographically vulnerable regions, are essential to ensure equitable access to diagnosis, care, and resource allocation. FundingY. Shen received partial support from NIH grants/contracts R35GM146612, R01AI170116, and 75N93019C00052.