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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.
  • Liu X; Ping An Healthcare Technology, Beijing, China.
  • Xu X; Ping An Healthcare Technology, Beijing, China.
  • Li G; Center for Global Health and Infectious Diseases, School of Medicine, Tsinghua University, Beijing, China.
  • Xu X; Ping An Healthcare Technology, Beijing, China.
  • Sun Y; Ping An Healthcare Technology, Beijing, China.
  • Wang F; Department of Healthcare Policy and Research, Weill Cornell Medicine, Cornell University, New York, USA.
  • Shi X; Center for Global Health and Infectious Diseases, School of Medicine, Tsinghua University, Beijing, China.
  • Li X; Ping An Healthcare Technology, Beijing, China. leeshore05@hotmail.com.
  • Xie G; Ping An Healthcare Technology, Beijing, China. xieguotong@pingan.com.cn.
  • Zhang L; Ping An Health Cloud Company Limited, Beijing, China. xieguotong@pingan.com.cn.
BMC Public Health ; 21(1): 965, 2021 05 21.
Article in English | MEDLINE | ID: covidwho-1238713
ABSTRACT

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 (Rt) 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 Rt and NPIs through a generalized linear model (GLM).

RESULTS:

Different NPIs were found to have led to different levels of reduction in Rt. 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 Rt 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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Public Health / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: North America Language: English Journal: BMC Public Health Journal subject: Public Health Year: 2021 Document Type: Article Affiliation country: S12889-021-10950-2

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Public Health / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: North America Language: English Journal: BMC Public Health Journal subject: Public Health Year: 2021 Document Type: Article Affiliation country: S12889-021-10950-2