4.6

CiteScore

2.2

Impact Factor
  • ISSN 1674-8301
  • CN 32-1810/R
Guan Jinxing, Wei Yongyue, Zhao Yang, Chen Feng. Modeling the transmission dynamics of COVID-19 epidemic: a systematic review[J]. The Journal of Biomedical Research, 2020, 34(6): 422-430. DOI: 10.7555/JBR.34.20200119
Citation: Guan Jinxing, Wei Yongyue, Zhao Yang, Chen Feng. Modeling the transmission dynamics of COVID-19 epidemic: a systematic review[J]. The Journal of Biomedical Research, 2020, 34(6): 422-430. DOI: 10.7555/JBR.34.20200119

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

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  • Corresponding author:

    Feng Chen, Department of Epidemiology and Biostatistics, School of Public Health, Center for Global Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, Jiangsu 211166, China. Tel: +86-25-86868436, E-mail: fengchen@njmu.edu.cn

  • Received Date: July 22, 2020
  • Revised Date: September 16, 2020
  • Accepted Date: September 24, 2020
  • Available Online: October 29, 2020
  • 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.
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