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Data-driven Analysis of the Simulations of the Spread of COVID-19 Under Different Interventions of China

Overview
Journal J Appl Stat
Specialty Public Health
Date 2023 Aug 2
PMID 37529566
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Abstract

Since February 2020, COVID-19 has spread rapidly to more than 200 countries in the world. During the pandemic, local governments in China have implemented different interventions to efficiently control the spread of the epidemic. Characterizing transmission of COVID-19 under some typical interventions is essential to help countries develop appropriate interventions. Based on the pre-symptomatic transmission patterns of COVID-19, we established a novel compartmental model: Susceptible-Infectious-Confirmed-Removed (SICR) model, which allowed the effective reproduction number to change over time, thus the effects of policies could be reasonably estimated. Using the epidemic data of Wuhan, Wenzhou, and Shenzhen, we migrated the corresponding estimated policy modes to South Korea, Italy, and the United States and simulated the potential outcomes for these countries when they adopted similar policy strategies to China. We found that the mild interventions implemented in Shenzhen were effective in controlling the epidemic in the early stage, while more stringent policies which were implemented in Wuhan and Wenzhou were necessary if the epidemic became severe and needed to be controlled in a short time.

Citing Articles

Editorial to the special issue: statistical perspectives on analytics for COVID-19 data.

Stromberg A, Chen J, Oliveira T, Zhao Y, Moghaddass R, Stehlik M J Appl Stat. 2023; 50(11-12):2287-2293.

PMID: 37529568 PMC: 10388801. DOI: 10.1080/02664763.2023.2228597.

References
1.
. Coronavirus Disease 2019 in Children - United States, February 12-April 2, 2020. MMWR Morb Mortal Wkly Rep. 2020; 69(14):422-426. PMC: 7147903. DOI: 10.15585/mmwr.mm6914e4. View

2.
Potterat J, Muth S, Rothenberg R, Green D, Taylor J, Bonney M . Chlamydia transmission: concurrency, reproduction number, and the epidemic trajectory. Am J Epidemiol. 1999; 150(12):1331-9. DOI: 10.1093/oxfordjournals.aje.a009965. View

3.
Chen S, Yang J, Yang W, Wang C, Barnighausen T . COVID-19 control in China during mass population movements at New Year. Lancet. 2020; 395(10226):764-766. PMC: 7159085. DOI: 10.1016/S0140-6736(20)30421-9. View

4.
Linden A, Mantyniemi S . Using the negative binomial distribution to model overdispersion in ecological count data. Ecology. 2011; 92(7):1414-21. DOI: 10.1890/10-1831.1. View

5.
Lauer S, Grantz K, Bi Q, Jones F, Zheng Q, Meredith H . The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Ann Intern Med. 2020; 172(9):577-582. PMC: 7081172. DOI: 10.7326/M20-0504. View