TY - JOUR
T1 - Social vulnerability and county stay-at-home behavior during COVID-19 stay-at-home orders, United States, April 7–April 20, 2020
AU - Fletcher, Kelly M.
AU - Espey, Julie
AU - Grossman, Marissa K.
AU - Sharpe, J. Danielle
AU - Curriero, Frank C.
AU - Wilt, Grete E.
AU - Sunshine, Gregory
AU - Moreland, Amanda
AU - Howard-Williams, Mara
AU - Ramos, J. Gabriel
AU - Giuffrida, Danilo
AU - García, Macarena C.
AU - Hartnett, William M.
AU - Foster, Stephanie
N1 - Funding Information:
The authors are grateful to Antonio Tomarchio; Brennan Lake; Cuebiq Data for Good Program; Charity Hilton; Samantha Lie-Tjauw, MBA, MPH; Jason Poovey, MS; Russell McCord, JD; GRASP Mobility Data Project Team; CDC Social Vulnerability Index Team; CDC Public Health Law Program; CDC COVID-19 Response. Proprietary data used in this study were provided to CDC/ATSDR by Cuebiq's Data for Good Program. This research was supported in part by an appointment to the Research Participation Program at the Centers for Disease Control and Prevention administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and CDC. This study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest.
Publisher Copyright:
© 2021
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
KW - COVID-19
KW - GIS
KW - Generalized linear mixed effect model
KW - Population movement
KW - Social vulnerability
KW - Spatial analysis
KW - Stay-at-home order
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U2 - 10.1016/j.annepidem.2021.08.020
DO - 10.1016/j.annepidem.2021.08.020
M3 - Article
C2 - 34500085
AN - SCOPUS:85118723694
SN - 1047-2797
VL - 64
SP - 76
EP - 82
JO - Annals of epidemiology
JF - Annals of epidemiology
ER -