Jung Sung-Mok, Akhmetzhanov Andrei R, Hayashi Katsuma, Linton Natalie M, Yang Yichi, Yuan Baoyin, Kobayashi Tetsuro, Kinoshita Ryo, Nishiura Hiroshi
Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan.
Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama 332-0012, Japan.
J Clin Med. 2020 Feb 14;9(2):523. doi: 10.3390/jcm9020523.
The exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number-the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December, 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% confidence interval [CI]: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.
在中国境外确诊的2019新型冠状病毒(COVID-19)感染病例为估计中国大陆的累积发病率和确诊病例病死率(cCFR)提供了契机。了解cCFR对于在疫情早期阶段描述COVID-19的严重程度和理解其大流行潜力至关重要。本研究利用发病率的指数增长率,对cCFR和基本繁殖数(即在易感人群中一个原发性病例产生的二代病例的平均数量)进行了统计学估计。我们根据2020年1月24日报告的20例境外输入病例的数据,建立了两种疫情增长模型:一种是从2019年12月8日发病的单个指示病例开始(情景1);另一种是使用与其他参数拟合的增长率(情景2)。1月24日中国的累积发病率估计分别为6924例(95%置信区间[CI]:4885,9211)和19289例(95%CI:10901,30158)。情景1中cCFR的最新估计值为5.3%(95%CI:3.5%,7.5%),情景2中为8.4%(95%CI:5.3%,12.3%)。情景1和情景2的基本繁殖数估计分别为2.1(95%CI:2.0,2.2)和3.2(95%CI:2.7,3.7)。基于这些结果,我们认为当前的COVID-19疫情具有引发大流行的巨大潜力。所提出的方法为利用公开可用数据进行早期风险评估提供了思路。