Serial Interval and Generation Interval for Imported and Local Infectors, Respectively, Estimated Using Reported Contact-Tracing Data of COVID-19 in China - Li, Menghui; Liu, Kai; Song, Yukun; Wang, Ming; Wu, Jinshan (Frontiers in Public Health, 2021)
The emerging virus, COVID-19, has caused a massive outbreak worldwide. Based on the publicly available contact-tracing data, we identified 509 transmission chains from 20 provinces in China and estimated the serial interval (SI) and generation interval (GI) of COVID-19 in China. Inspired by possibly different values of the time-varying reproduction number for the imported cases and the local cases in China, we divided all transmission events into three subsets: imported (the zeroth generation) infecting 1st-generation locals, 1st-generation locals infecting 2nd-generation locals, and others transmissions among 2+. The corresponding SI (GI) is respectively denoted as SI^0_1(GI^0_1), SI^1_2 (GI^1_2), and SI^2+_3+(GI^2+_3+). A Bayesian approach with doubly interval-censored likelihood is employed to fit the distribution function of the SI and GI. It is found that the estimated SI^0_1=6.52(95%CI: 5.96-7.13), SI^1_2=6.01(95%CI: 5.44-6.64), SI^2+_3+=4.39(95%CI: 3.74-5.15), and GI^0_1=5.47(95%CI: 4.57-6.45), GI^1_2=5.01(95%CI: 3.58-7.06), GI^2+_3+=4.25 (95%CI: 2.82-6.23). Thus overall both SI and GI decrease when generation increases.