Open AccessDifferences in how interventions coupled with effective reproduction numbers account for marked variations in COVID-19 epidemic outcomes
Author(s) -
Fan Xia,
Yanni Xiao,
Peiyu Liu,
Robert Cheke,
Xuanya Li
Publication year - 2020
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2020274
Subject(s) - mainland china , quarantine , pandemic , psychological intervention , isolation (microbiology) , outbreak , social distance , covid-19 , china , demography , basic reproduction number , geography , environmental health , business , medicine , biology , disease , sociology , virology , population , microbiology and biotechnology , archaeology , pathology , psychiatry , infectious disease (medical specialty)
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 R t 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 R t 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.