Selected article for: "disease onset and incubation period"
Author: Zhu, Yifan; Chen, Ying Qing
Title: On a Statistical Transmission Model in Analysis of the Early Phase of COVID-19 Outbreak
  • Cord-id: gt247nwe
  • Document date: 2020_4_2
    • ID: gt247nwe
    Snippet: 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
    Document: 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 [Formula: see text] 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 [Formula: see text] were also reported. Potential issues such as data quality concerns and comparison of different modelling approaches were discussed. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12561-020-09277-0) contains supplementary material, which is available to authorized users.

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