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Social vulnerability and county stay-at-home behavior during COVID-19 stay-at-home orders, United States, April 7–April 20, 2020
- Source :
- Annals of Epidemiology
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- Purpose Early COVID-19 mitigation relied on people staying home except for essential trips. The ability to stay home may differ by sociodemographic factors. We analyzed how factors related to social vulnerability impact a community's ability to stay home during a stay-at-home order. Methods Using generalized, linear mixed models stratified by stay-at-home order (mandatory or not mandatory), we analyzed county-level stay-at-home behavior (inferred from mobile devices) during a period when a majority of United States counties had stay-at-home orders (April 7–April 20, 2020) with the Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI). Results Counties with higher percentages of single-parent households, mobile homes, and persons with lower educational attainment were associated with lower stay-at-home behavior compared with counties with lower respective percentages. Counties with higher unemployment, higher percentages of limited-English-language speakers, and more multi-unit housing were associated with increases in stay-at-home behavior compared with counties with lower respective percentages. Stronger effects were found in counties with mandatory orders. Conclusions Sociodemographic factors impact a community's ability to stay home during COVID-19 stay-at-home orders. Communities with higher social vulnerability may have more essential workers without work-from-home options or fewer resources to stay home for extended periods, which may increase risk for COVID-19. Results are useful for tailoring messaging, COVID-19 vaccine delivery, and public health responses to future outbreaks.
- Subjects :
- medicine.medical_specialty
COVID-19 Vaccines
Index (economics)
Social vulnerability
Coronavirus disease 2019 (COVID-19)
Epidemiology
media_common.quotation_subject
Population movement
medicine
Humans
media_common
SARS-CoV-2
business.industry
Public health
Spatial analysis
COVID-19
Vaccine delivery
GIS
Disease control
Stay-at-home order
United States
Educational attainment
Unemployment
Original Article
business
Generalized linear mixed effect model
Demography
Subjects
Details
- ISSN :
- 10472797
- Volume :
- 64
- Database :
- OpenAIRE
- Journal :
- Annals of Epidemiology
- Accession number :
- edsair.doi.dedup.....80044a3b0f2039f6a0aa62dd38d50aa1
- Full Text :
- https://doi.org/10.1016/j.annepidem.2021.08.020