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State variation in effects of state social distancing policies on COVID-19 cases
BACKGROUND: The novel coronavirus disease 2019 (COVID-19) sickened over 20 million residents in the United States (US) by January 2021. Our objective was to describe state variation in the effect of initial social distancing policies and non-essential business (NEB) closure on infection rates early...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8237534/ https://www.ncbi.nlm.nih.gov/pubmed/34182972 http://dx.doi.org/10.1186/s12889-021-11236-3 |
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author | Kaufman, Brystana G. Whitaker, Rebecca Mahendraratnam, Nirosha Hurewitz, Sophie Yi, Jeremy Smith, Valerie A. McClellan, Mark |
author_facet | Kaufman, Brystana G. Whitaker, Rebecca Mahendraratnam, Nirosha Hurewitz, Sophie Yi, Jeremy Smith, Valerie A. McClellan, Mark |
author_sort | Kaufman, Brystana G. |
collection | PubMed |
description | BACKGROUND: The novel coronavirus disease 2019 (COVID-19) sickened over 20 million residents in the United States (US) by January 2021. Our objective was to describe state variation in the effect of initial social distancing policies and non-essential business (NEB) closure on infection rates early in 2020. METHODS: We used an interrupted time series study design to estimate the total effect of all state social distancing orders, including NEB closure, shelter-in-place, and stay-at-home orders, on cumulative COVID-19 cases for each state. Data included the daily number of COVID-19 cases and deaths for all 50 states and Washington, DC from the New York Times database (January 21 to May 7, 2020). We predicted cumulative daily cases and deaths using a generalized linear model with a negative binomial distribution and a log link for two models. RESULTS: Social distancing was associated with a 15.4% daily reduction (Relative Risk = 0.846; Confidence Interval [CI] = 0.832, 0.859) in COVID-19 cases. After 3 weeks, social distancing prevented nearly 33 million cases nationwide, with about half (16.5 million) of those prevented cases among residents of the Mid-Atlantic census division (New York, New Jersey, Pennsylvania). Eleven states prevented more than 10,000 cases per 100,000 residents within 3 weeks. CONCLUSIONS: The effect of social distancing on the infection rate of COVID-19 in the US varied substantially across states, and effects were largest in states with highest community spread. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-11236-3. |
format | Online Article Text |
id | pubmed-8237534 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-82375342021-06-28 State variation in effects of state social distancing policies on COVID-19 cases Kaufman, Brystana G. Whitaker, Rebecca Mahendraratnam, Nirosha Hurewitz, Sophie Yi, Jeremy Smith, Valerie A. McClellan, Mark BMC Public Health Research Article BACKGROUND: The novel coronavirus disease 2019 (COVID-19) sickened over 20 million residents in the United States (US) by January 2021. Our objective was to describe state variation in the effect of initial social distancing policies and non-essential business (NEB) closure on infection rates early in 2020. METHODS: We used an interrupted time series study design to estimate the total effect of all state social distancing orders, including NEB closure, shelter-in-place, and stay-at-home orders, on cumulative COVID-19 cases for each state. Data included the daily number of COVID-19 cases and deaths for all 50 states and Washington, DC from the New York Times database (January 21 to May 7, 2020). We predicted cumulative daily cases and deaths using a generalized linear model with a negative binomial distribution and a log link for two models. RESULTS: Social distancing was associated with a 15.4% daily reduction (Relative Risk = 0.846; Confidence Interval [CI] = 0.832, 0.859) in COVID-19 cases. After 3 weeks, social distancing prevented nearly 33 million cases nationwide, with about half (16.5 million) of those prevented cases among residents of the Mid-Atlantic census division (New York, New Jersey, Pennsylvania). Eleven states prevented more than 10,000 cases per 100,000 residents within 3 weeks. CONCLUSIONS: The effect of social distancing on the infection rate of COVID-19 in the US varied substantially across states, and effects were largest in states with highest community spread. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-11236-3. BioMed Central 2021-06-28 /pmc/articles/PMC8237534/ /pubmed/34182972 http://dx.doi.org/10.1186/s12889-021-11236-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Kaufman, Brystana G. Whitaker, Rebecca Mahendraratnam, Nirosha Hurewitz, Sophie Yi, Jeremy Smith, Valerie A. McClellan, Mark State variation in effects of state social distancing policies on COVID-19 cases |
title | State variation in effects of state social distancing policies on COVID-19 cases |
title_full | State variation in effects of state social distancing policies on COVID-19 cases |
title_fullStr | State variation in effects of state social distancing policies on COVID-19 cases |
title_full_unstemmed | State variation in effects of state social distancing policies on COVID-19 cases |
title_short | State variation in effects of state social distancing policies on COVID-19 cases |
title_sort | state variation in effects of state social distancing policies on covid-19 cases |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8237534/ https://www.ncbi.nlm.nih.gov/pubmed/34182972 http://dx.doi.org/10.1186/s12889-021-11236-3 |
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