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

Pub Date : 2021-01-01 Epub Date: 2020-04-02 DOI:10.1007/s12561-020-09277-0
Yifan Zhu, Ying Qing Chen
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引用次数: 52

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 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 were also reported. Potential issues such as data quality concerns and comparison of different modelling approaches were discussed.

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基于统计传播模型的新冠肺炎疫情早期分析
自2019年12月以来,一种新型冠状病毒(COVID-19)引起的疾病感染了许多人,截至2020年3月17日,累计确诊病例已接近18万例。据信,新冠肺炎疫情是在中国湖北省人口超过1100万的大都市武汉的一个海鲜市场爆发的。我们引入了统计疾病传播模型,利用病例症状发作数据估计中国早期疫情的传播力,并对COVID-19疾病自然史的各种假设进行了敏感性分析。我们将传播模型拟合到2020年2月11日之前的几个公开来源的疫情数据,并估计了武汉市的封锁干预效果。根据潜伏期和传染期内相对传染性的合理分布假设,估计r0在2.7至4.2之间。95%置信区间r0也有报道。讨论了诸如数据质量问题和不同建模方法的比较等潜在问题。
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