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Differences in how interventions coupled with effective reproduction numbers account for marked variations in COVID-19 epidemic outcomes

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Title: Differences in how interventions coupled with effective reproduction numbers account for marked variations in COVID-19 epidemic outcomes
Authors: Xia, F
Xiao, Y
Liu, P
A. Cheke, R
Li, X
Item Type: Journal Article
Abstract: The COVID-19 outbreak, designated a “pandemic” by the World Health Organization (WHO) on 11 March 2020, has spread worldwide rapidly. Each country implemented prevention and control strategies, mainly classified as SARS LCS (SARS-like containment strategy) or PAIN LMS (pandemic influenza-like mitigation strategy). The reasons for variation in each strategy’s efficacy in controlling COVID-19 epidemics were unclear and are investigated in this paper. On the basis of the daily number of confirmed local (imported) cases and onset-to-confirmation distributions for local cases, we initially estimated the daily number of local (imported) illness onsets by a deconvolution method for mainland China, South Korea, Japan and Spain, and then estimated the effective reproduction numbers Rt by using a Bayesian method for each of the four countries. China and South Korea adopted a strict SARS LCS, to completely block the spread via lockdown, strict travel restrictions and by detection and isolation of patients, which led to persistent declines in effective reproduction numbers. In contrast, Japan and Spain adopted a typical PAIN LMS to mitigate the spread via maintaining social distance, self-quarantine and isolation etc., which reduced the Rt values but with oscillations around 1. The finding suggests that governments may need to consider multiple factors such as quantities of medical resources, the likely extent of the public’s compliance to different intensities of intervention measures, and the economic situation to design the most appropriate policies to fight COVID-19 epidemics.
Issue Date: 27-Jul-2020
Date of Acceptance: 21-Jul-2020
URI: http://hdl.handle.net/10044/1/83899
DOI: 10.3934/mbe.2020274
ISSN: 1551-0018
Publisher: American Institute of Mathematical Sciences (AIMS)
Start Page: 5085
End Page: 5098
Journal / Book Title: Mathematical Biosciences and Engineering
Volume: 17
Issue: 5
Copyright Statement: © 2020 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
Keywords: Bioinformatics
0102 Applied Mathematics
0903 Biomedical Engineering
0904 Chemical Engineering
Publication Status: Published
Online Publication Date: 2020-07-27
Appears in Collections:Imperial College London COVID-19
School of Public Health



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