| 杜志成,顾菁,李菁华,林晓,王莹,陈龙,郝元涛.基于区间删失数据估计方法的COVID-19潜伏期分布估计[J].Chinese journal of Epidemiology,2020,41(7):1000-1003 |
| 基于区间删失数据估计方法的COVID-19潜伏期分布估计 |
| Estimating the distribution of COVID-19 incubation period by interval-censored data estimation method |
| Received:March 13, 2020 |
| DOI：10.3760/cma.j.cn112338-20200313-00331 |
| KeyWord: 新型冠状病毒肺炎 潜伏期 区间删失数据估计方法 |
| English Key Word: COVID-19 Incubation period Interval-censored data estimation method |
| FundProject:国家自然科学基金（81773543，81973150）；中山大学2020年度“三大”建设大科研项目培育专项 |
| Author Name | Affiliation | E-mail | | Du Zhicheng | Department of Medical Statistics and Health Information Research Centre, Guangdong Key Laboratory of Health Informatics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China | | | Gu Jing | Department of Medical Statistics and Health Information Research Centre, Guangdong Key Laboratory of Health Informatics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510275, China | | | Li Jinghua | Department of Medical Statistics and Health Information Research Centre, Guangdong Key Laboratory of Health Informatics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510275, China | | | Lin Xiao | Department of Medical Statistics and Health Information Research Centre, Guangdong Key Laboratory of Health Informatics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China | | | Wang Ying | Department of Medical Statistics and Health Information Research Centre, Guangdong Key Laboratory of Health Informatics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China | | | Chen Long | Government Affairs Service Center, Health Commission of Guangdong Province, Guangzhou 510060, China | | | Hao Yuantao | Department of Medical Statistics and Health Information Research Centre, Guangdong Key Laboratory of Health Informatics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510275, China | haoyt@mail.sysu.edu.cn |
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| Abstract: |
| 目的 新型冠状病毒肺炎疫情已经成为全球关注的公共卫生问题，其潜伏期等流行病学特征尚不明确，本研究旨在对新型冠状病毒肺炎的潜伏期分布进行估计。方法 收集各省份卫生健康委员会官方发布信息平台的确诊病例暴露与发病信息，利用区间删失数据估计方法，基于Log-normal、Gamma和Weibull分布，对新型冠状病毒肺炎的潜伏期分布进行估计。结果 本研究共收集确诊病例109例，平均年龄为39.825岁。基于Log-normal分布的潜伏期M=4.938（P25～P75：3.451～7.304）d，Gamma分布的潜伏期M=5.064（P25～P75：3.489～7.301）d，Weibull分布的潜伏期M=5.678（P25～P75：3.653～7.666）d。Gamma分布的对数似然函数值最大。结论 COVID-19的潜伏期服从Gamma分布，基于区间删失数据的估计方法可用于传染病潜伏期分布的估计。 |
| English Abstract: |
| Objectives The COVID-19 has been the public health issues of global concern, but the incubation period was still under discussion. This study aimed to estimate the incubation period distribution of COVID-19. Methods The exposure and onset information of COVID-19 cases were collected from the official information platform of provincial or municipal health commissions. The distribution of COVID-19 incubation period was estimated based on the Log-normal, Gamma and Weibull distribution by interval-censored data estimation method. Results A total of 109 confirmed cases were collected, with an average age of 39.825 years. The median COVID-19 incubation period based on Log-normal, Gamma, and Weibull distribution were 4.958 (P25-P75:3.472-7.318) days, 5.083 (P25-P75:3.511-7.314) days, and 5.695 (P25-P75:3.675-7.674) days, respectively. Gamma distribution had the largest log-likelihood result. Conclusions The distribution of COVID-19 incubation period followed the Gamma distribution, and the interval-censored data estimation method can be used to estimate the incubation period distribution. |
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