Impact of the Timing of Stay-at-Home Orders and Mobility Reductions on First-Wave COVID-19 Deaths in US Counties.

Content Provider	Europe PMC
Author	Audirac, Michelle Tec, Mauricio Meyers, Lauren Ancel Fox, Spencer Zigler, Cory
Copyright Year	2022
Abstract	AbstractAs SARS-CoV-2 transmission continues to evolve, understanding how location-specific variations in non-pharmaceutical interventions and behaviors contributed to disease transmission during the initial epidemic wave will be key for future control strategies. We offer a rigorous statistical analysis of the relative effectiveness of the timing of both official stay-at-home orders and population mobility reductions during the initial stage of the US epidemic. We use a Bayesian hierarchical regression to fit county-level mortality data from the first case on Jan 21 2020 through Apr 20 2020 and quantify associations between the timing of stay-at-home orders and population mobility with epidemic control. We find that among 882 counties with an early local epidemic, a 10-day delay in the enactment of stay-at-home orders would have been associated with 14,700 additional deaths by Apr 20 (95% credible interval, 9,100, 21,500), whereas shifting orders 10 days earlier would have been associated with nearly 15,700 fewer lives lost (95% credible interval, 11,350, 18,950). Analogous estimates are available for reductions in mobility—which typically occurred before stay-at-home orders—and are also stratified by county urbanicity, showing significant heterogeneity. Results underscore the importance of timely policy and behavioral action for early-stage epidemic control.
Related Links	https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC8903416&blobtype=pdf
ISSN	00029262
Journal	American Journal of Epidemiology [Am J Epidemiol]
Volume Number	191
DOI	10.1093/aje/kwac027
PubMed Central reference number	PMC8903416
Issue Number	5
PubMed reference number	35136914
e-ISSN	14766256
Language	English
Publisher	Oxford University Press
Publisher Date	2022-03-01
Access Restriction	Open
Rights License	This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) © The Author(s) 2022. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
Subject Keyword	Bayesian hierarchical model counterfactuals SARS-COV-2 intervention analysis non- pharmaceutical interventions stay-at-home orders Covid-19
Content Type	Text
Resource Type	Article
Subject	Epidemiology