Estimating the distribution of COVID-19 incubation period by interval-censored data estimation method
10.3760/cma.j.cn112338-20200313-00331
- VernacularTitle:基于区间删失数据估计方法的COVID-19潜伏期分布估计
- Author:
Zhicheng DU
1
;
Jing GU
;
Jinghua LI
;
Xiao LIN
;
Ying WANG
;
Long CHEN
;
Yuantao HAO
Author Information
1. 中山大学公共卫生学院医学统计系，卫生信息研究中心，广东省卫生信息学重点实验室，广州 510080
- Keywords:
COVID-19;
Incubation period;
Interval-censored data estimation method
- From:
Chinese Journal of Epidemiology
2020;41(7):1000-1003
- CountryChina
- Language:Chinese
-
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.
