Department of Sociology and Criminology, Pennsylvania State University, University Park, PA, USA; Population Research Institute, Pennsylvania State University, University Park, PA, USA.
College of Information Science and Technology, Pennsylvania State University, University Park, PA, USA.
Health Place. 2022 Sep;77:102891. doi: 10.1016/j.healthplace.2022.102891. Epub 2022 Aug 11.
Biweekly county COVID-19 data were linked with Longitudinal Employer-Household Dynamics data to analyze population risk exposures enabled by pre-pandemic, country-wide commuter networks. Results from fixed-effects, spatial, and computational statistical approaches showed that commuting network exposure to COVID-19 predicted an area's COVID-19 cases and deaths, indicating spillovers. Commuting spillovers between counties were independent from geographic contiguity, pandemic-time mobility, or social media ties. Results suggest that commuting connections form enduring social linkages with effects on health that can withstand mobility disruptions. Findings contribute to a growing relational view of health and place, with implications for neighborhood effects research and place-based policies.
双周刊县级 COVID-19 数据与纵向雇主-家庭动态数据相链接，以分析由全国性的大流行前通勤网络带来的人口风险暴露。固定效应、空间和计算统计方法的结果表明，通勤网络接触新冠病毒会预测一个地区的新冠病毒病例和死亡人数，表明存在溢出效应。县与县之间的通勤溢出与地理毗邻、大流行时期的流动性或社交媒体关系无关。结果表明，通勤联系形成了持久的社会联系，对健康产生影响，可以抵御流动性的干扰。研究结果为健康和地点的关系视角提供了新的认识，对邻里效应研究和基于地点的政策具有启示意义。
