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Connected in health: Place-to-place commuting networks and COVID-19 spillovers.
Seto, Christopher H; Graif, Corina; Khademi, Aria; Honavar, Vasant G; Kelling, Claire E.
  • Seto CH; Department of Sociology and Criminology, Pennsylvania State University, University Park, PA, USA; Population Research Institute, Pennsylvania State University, University Park, PA, USA. Electronic address: chs37@psu.edu.
  • Graif C; Department of Sociology and Criminology, Pennsylvania State University, University Park, PA, USA; Population Research Institute, Pennsylvania State University, University Park, PA, USA. Electronic address: corina.graif@psu.edu.
  • Khademi A; College of Information Science and Technology, Pennsylvania State University, University Park, PA, USA.
  • Honavar VG; College of Information Science and Technology, Pennsylvania State University, University Park, PA, USA; Center for Big Data Analytics and Discovery Informatics, Pennsylvania State University, University Park, PA, USA; Institute for Computational and Data Sciences, Pennsylvania State University, Univ
  • Kelling CE; Department of Statistics, Pennsylvania State University, University Park, PA, USA.
Health Place ; 77: 102891, 2022 09.
Article in English | MEDLINE | ID: covidwho-1983101
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Health Place Journal subject: Epidemiology / Public Health Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Health Place Journal subject: Epidemiology / Public Health Year: 2022 Document Type: Article