Estimation of incubation period distribution of COVID-19 using disease onset forward time: a novel cross-sectional and forward follow-up study

Qin Jing; Chong You; Qiushi Lin; Taojun Hu; Shicheng Yu; Xiao-Hua Zhou

is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.06.20032417 doi: medRxiv preprint be observed and hence lead to an underestimation. Linton et al proposed a similar approach to estimate the incubation period of Backer et al, but corrected the aforementioned second sampling bias. 5, 6 However, the first problem in regard to sampling bias is still an unsolved issue. The estimates of the incubation period from these four studies, together with other results of two other coronavirus disease, SARS and MERS, are listed in Table 1 . To overcome the aforementioned problems, we propose a novel method to estimate the incubation period of COVID-19 by using the well-known renewal theory in probability. 18 Such a method enhances the accuracy of estimation by reducing recall bias and utilizing abundance of the readily available forward time with a large sample size of 1211. To the best of our knowledge, this paper is a study of the distribution of the incubation period involving the largest number of samples to date. We find the estimated median of the incubation period is 8·13 days (95% CI: 7·37-8·91), and mean is 8·62 days (95% CI: 8·02-9·28), the 90th percentile is 14·65 days (95% CI: 14·00-15·26), and the 99th percentile is 20·59