Incubation Period of Coronavirus Disease 2019: New Implications for Intervention and Control

Abstract

Background: The COVID-19 pandemic raging around the world has caused serious disasters to mankind. The incubation period is a key parameter for epidemic control and also an important basis for epidemic prediction, but its distribution law remain unclear. Methods: The incubation period T was described by the accelerated failure time models, and the principle of interval-censored data processing and estimation methods were used. Statistical analysis were performed on R-4.0.2 software using “coarseDataTools 0.6-5” package to optimize the parameters to be estimated and calculate the confidence interval. The optimization method used when solving the maximum likelihood function is the simplex method. We used bootstrap re-sampling procedures with 1000 iterations to estimate the confidence interval. Results: Here we analyzed the epidemiological information of 787 confirmed non-Wuhan resident cases, and systematically studied the characteristics of the incubation period of COVID-19 based on the interval-censored data estimation method. Through the statistical analysis of the overall and 7 types of sub-group samples, it was concluded that the incubation period of COVID-19 approximately conformed to the Gamma distribution with a mean value of 7.8 (95%CI: 7.4-8.5) days and a median value of 7.0 (95%CI: 6.7-7.3) days. Conclusions: The incubation period was positively correlated with age and negatively correlated with disease severity. Female cases presented a slightly higher incubation period than that of males. The incubation period of cases with travel history to Hubei and multiple exposures was shorter. The proportion of infected persons who developed symptoms within 14 days was 91.6%. These results are of great significance to the prevention and control of the COVID-19 pandemic.