Chen Zhetao, Li Bingnan, Chen Yewen, Liu Jialing, Luo Fangzhi, Ogunyemi Kehinde Olawale, Ge Yang, Ke Yuan, Yang Yang, Chen Xianyan, Shen Ye
Epidemiology & Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA.
Department of Statistics, Franklin College of Arts and Science, University of Georgia, Athens, GA, USA.
medRxiv. 2025 Aug 26:2025.08.21.25334183. doi: 10.1101/2025.08.21.25334183.
Long 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.
This 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 variant's emergence, and spatial patterns were assessed using Moran's 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.
Quarterly 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 Omicron's 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.
These 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.
Y. Shen received partial support from NIH grants/contracts R35GM146612, R01AI170116, and 75N93019C00052.
长期新冠影响了相当一部分美国人口，但其时空分布仍未得到充分描述。奥密克戎变异株的出现以及持续存在的社会人口差异可能导致长期新冠风险的区域差异。了解长期新冠的模式对于实施有针对性且公平的公共卫生干预措施至关重要。
这项回顾性研究利用了来自国家新冠队列协作组织（N3C）的数据，涵盖了2021年至2024年美国1063个县的5652474例新冠病例和41694例长期新冠病例。分析了奥密克戎变异株出现前后长期新冠的时间模式，并使用莫兰指数（Moran's I）和Getis统计量评估空间模式。采用贝叶斯空间随机效应模型来评估长期新冠发病率与经济脆弱性、医疗服务可及性和流动性等社会人口因素之间的关联。
长期新冠的季度发病率在0.015%至14.29%之间。在奥密克戎变异株出现之前，发病率为每10000例新冠病例中有204例，而在奥密克戎出现后为每10000例新冠病例中有248例（p<0.001）。奥密克戎出现后，48.8%[673个县中的328个]的县显示出显著的空间相关性（p<0.05），高于之前的43.5%[673个县中的293个]。高风险地区变得更加集中在内陆地区，而低风险地区则聚集在东海岸沿线。长期新冠发病率与经济脆弱性、医疗服务可及性有限和流动性限制显著相关，这些社会人口差异随着时间的推移持续推动其空间差异。
这些发现强调了应对长期新冠风险中的空间和社会不平等问题的必要性。有针对性的公共卫生干预措施，特别是在经济和地理上脆弱的地区，对于确保公平获得诊断、护理和资源分配至关重要。
沈洋获得了美国国立卫生研究院（NIH）的资助/合同R35GM146612、R01AI170116和75N93019C00052的部分支持。
