Serial Interval and Generation Interval for Imported and Local Infectors, Respectively, Estimated Using Reported Contact-Tracing Data of COVID-19 in China.

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 different possible 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 other transmissions among 2+. The corresponding SI (GI) is respectively denoted as SI 1 0 ( GI 1 0 ), SI 2 1 ( GI 2 1 ), and SI 3 + 2 + ( GI 3 + 2 + ). A Bayesian approach with doubly interval-censored likelihood is employed to fit the distribution function of the SI and GI. It was found that the estimated SI 1 0 = 6 . 52   ( 95 %   CI : 5 . 96 - 7 . 13 ) , SI 2 1 = 6 . 01   ( 95 % CI : 5 . 44 - 6 . 64 ) , SI 3 + 2 + = 4 . 39   ( 95 %   CI : 3 . 74 - 5 . 15 ) , and GI 1 0 = 5 . 47   ( 95 %   CI : 4 . 57 - 6 . 45 ) , GI 2 1 = 5 . 01   ( 95 %   CI : 3 . 58 - 7 . 06 ) , GI 3 + 2 + = 4 . 25   ( 95 %   CI : 2 . 82 - 6 . 23 ) . Thus, overall both SI and GI decrease when generation increases.