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On a Statistical Transmission Model in Analysis of the Early Phase of COVID-19 Outbreak

Author

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  • Yifan Zhu

    (Fred Hutchinson Cancer Research Center)

  • Ying Qing Chen

    (Fred Hutchinson Cancer Research Center)

Abstract

Since December 2019, a disease caused by a novel strain of coronavirus (COVID-19) had infected many people and the cumulative confirmed cases have reached almost 180,000 as of 17, March 2020. The COVID-19 outbreak was believed to have emerged from a seafood market in Wuhan, a metropolis city of more than 11 million population in Hubei province, China. We introduced a statistical disease transmission model using case symptom onset data to estimate the transmissibility of the early-phase outbreak in China, and provided sensitivity analyses with various assumptions of disease natural history of the COVID-19. We fitted the transmission model to several publicly available sources of the outbreak data until 11, February 2020, and estimated lock down intervention efficacy of Wuhan city. The estimated $$R_0$$ R 0 was between 2.7 and 4.2 from plausible distribution assumptions of the incubation period and relative infectivity over the infectious period. 95% confidence interval of $$R_0$$ R 0 were also reported. Potential issues such as data quality concerns and comparison of different modelling approaches were discussed.

Suggested Citation

  • Yifan Zhu & Ying Qing Chen, 2021. "On a Statistical Transmission Model in Analysis of the Early Phase of COVID-19 Outbreak," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(1), pages 1-17, April.
    • Handle: RePEc:spr:stabio:v:13:y:2021:i:1:d:10.1007_s12561-020-09277-0
    DOI: 10.1007/s12561-020-09277-0
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    Cited by:

    1. Huo, Liang’an & Gu, Jiafeng, 2023. "The influence of individual emotions on the coupled model of unconfirmed information propagation and epidemic spreading in multilayer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).

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