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. 2020 Oct 30;34(6):422-430.
doi: 10.7555/JBR.34.20200119.

Modeling the transmission dynamics of COVID-19 epidemic: a systematic review

Jinxing Guan  1 , Yongyue Wei  1 , Yang Zhao  1 , Feng Chen  1
Affiliations

Modeling the transmission dynamics of COVID-19 epidemic: a systematic review

Jinxing Guan et al. J Biomed Res. .

Abstract

The outbreak and rapid spread of COVID-19 has become a public health emergency of international concern. A number of studies have used modeling techniques and developed dynamic models to estimate the epidemiological parameters, explore and project the trends of the COVID-19, and assess the effects of intervention or control measures. We identified 63 studies and summarized the three aspects of these studies: epidemiological parameters estimation, trend prediction, and control measure evaluation. Despite the discrepancy between the predictions and the actuals, the dynamic model has made great contributions in the above three aspects. The most important role of dynamic models is exploring possibilities rather than making strong predictions about longer-term disease dynamics.

Keywords: COVID-19; SEIR model; SIR model; coronavirus; epidemiology modeling; transmission dynamic model.

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Figures

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Illustration of transmission dynamic models.
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PRISMA flow diagram.
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Overview of studies.
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Parameter settings.
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The deviation of trend prediction.
See this image and copyright information in PMC

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