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

Yifan Zhu () and Ying Qing Chen ()
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Yifan Zhu: Fred Hutchinson Cancer Research Center
Ying Qing Chen: Fred Hutchinson Cancer Research Center

Statistics in Biosciences, 2021, vol. 13, issue 1, No 1, 17 pages

Abstract: 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.

Keywords: COVID-19; Transmission model; Basic reproduction number; Emerging outbreak (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s12561-020-09277-0

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