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Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States

BACKGROUND: The widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs), such as non-essential busin...

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Autores principales: Liu, Xiaoshuang, Xu, Xiao, Li, Guanqiao, Xu, Xian, Sun, Yuyao, Wang, Fei, Shi, Xuanling, Li, Xiang, Xie, Guotong, Zhang, Linqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139542/
https://www.ncbi.nlm.nih.gov/pubmed/34020613
http://dx.doi.org/10.1186/s12889-021-10950-2
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author Liu, Xiaoshuang
Xu, Xiao
Li, Guanqiao
Xu, Xian
Sun, Yuyao
Wang, Fei
Shi, Xuanling
Li, Xiang
Xie, Guotong
Zhang, Linqi
author_facet Liu, Xiaoshuang
Xu, Xiao
Li, Guanqiao
Xu, Xian
Sun, Yuyao
Wang, Fei
Shi, Xuanling
Li, Xiang
Xie, Guotong
Zhang, Linqi
author_sort Liu, Xiaoshuang
collection PubMed
description BACKGROUND: The widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs), such as non-essential business closures and gathering bans, to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is greatly needed to assist in guiding individualized decision making for adjustment of interventions in the US and around the world. However, the impacts of these approaches remain uncertain. METHODS: Based on the reported cases, the effective reproduction number (R(t)) of COVID-19 epidemic for 50 states in the US was estimated. Measurements on the effectiveness of nine different NPIs were conducted by assessing risk ratios (RRs) between R(t) and NPIs through a generalized linear model (GLM). RESULTS: Different NPIs were found to have led to different levels of reduction in R(t). Stay-at-home contributed approximately 51% (95% CI 46–57%), wearing (face) masks 29% (15–42%), gathering ban (more than 10 people) 19% (14–24%), non-essential business closure 16% (10–21%), declaration of emergency 13% (8–17%), interstate travel restriction 11% (5–16%), school closure 10% (7–14%), initial business closure 10% (6–14%), and gathering ban (more than 50 people) 7% (2–11%). CONCLUSIONS: This retrospective assessment of NPIs on R(t) has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-10950-2.
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spelling pubmed-81395422021-05-24 Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States Liu, Xiaoshuang Xu, Xiao Li, Guanqiao Xu, Xian Sun, Yuyao Wang, Fei Shi, Xuanling Li, Xiang Xie, Guotong Zhang, Linqi BMC Public Health Research Article BACKGROUND: The widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs), such as non-essential business closures and gathering bans, to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is greatly needed to assist in guiding individualized decision making for adjustment of interventions in the US and around the world. However, the impacts of these approaches remain uncertain. METHODS: Based on the reported cases, the effective reproduction number (R(t)) of COVID-19 epidemic for 50 states in the US was estimated. Measurements on the effectiveness of nine different NPIs were conducted by assessing risk ratios (RRs) between R(t) and NPIs through a generalized linear model (GLM). RESULTS: Different NPIs were found to have led to different levels of reduction in R(t). Stay-at-home contributed approximately 51% (95% CI 46–57%), wearing (face) masks 29% (15–42%), gathering ban (more than 10 people) 19% (14–24%), non-essential business closure 16% (10–21%), declaration of emergency 13% (8–17%), interstate travel restriction 11% (5–16%), school closure 10% (7–14%), initial business closure 10% (6–14%), and gathering ban (more than 50 people) 7% (2–11%). CONCLUSIONS: This retrospective assessment of NPIs on R(t) has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-10950-2. BioMed Central 2021-05-21 /pmc/articles/PMC8139542/ /pubmed/34020613 http://dx.doi.org/10.1186/s12889-021-10950-2 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
Liu, Xiaoshuang
Xu, Xiao
Li, Guanqiao
Xu, Xian
Sun, Yuyao
Wang, Fei
Shi, Xuanling
Li, Xiang
Xie, Guotong
Zhang, Linqi
Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States
title Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States
title_full Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States
title_fullStr Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States
title_full_unstemmed Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States
title_short Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States
title_sort differential impact of non-pharmaceutical public health interventions on covid-19 epidemics in the united states
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139542/
https://www.ncbi.nlm.nih.gov/pubmed/34020613
http://dx.doi.org/10.1186/s12889-021-10950-2
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