Social vulnerability and county stay-at-home behavior during COVID-19 stay-at-home orders, United States, April 7–April 20, 2020

Kelly M. Fletcher, Julie Espey, Marissa K. Grossman, J. Danielle Sharpe, Frank C. Curriero, Grete E. Wilt, Gregory Sunshine, Amanda Moreland, Mara Howard-Williams, J. Gabriel Ramos, Danilo Giuffrida, Macarena C. García, William M. Hartnett, Stephanie Foster

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)76-82
Number of pages7
JournalAnnals of epidemiology
Volume64
DOIs
StatePublished - Dec 2021

Keywords

  • COVID-19
  • GIS
  • Generalized linear mixed effect model
  • Population movement
  • Social vulnerability
  • Spatial analysis
  • Stay-at-home order

ASJC Scopus subject areas

  • Epidemiology

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