Estimating the serial interval of the novel coronavirus disease (COVID 19) A statistical analysis using the public data in Hong Kong from January 16 to February 15, 2020
Backgrounds: The emerging virus, severe acute respiratory syndrome coronavirus 2 (SARS CoV 2) has caused a large outbreak of novel coronavirus disease (COVID 19) in Wuhan, China since December 2019. Based on the publicly available surveillance data, we identified 21 transmission chains in Hong Kong and estimated the serial interval (SI) of COVID 19. Methods: Index cases were identified and reported after symptoms onset, and contact tracing was conducted to collect the data of the associated secondary cases. An interval censored likelihood framework is adopted to fit a Gamma distribution function to govern the SI of COVID 19. Findings: Assuming a Gamma distributed model, we estimated the mean of SI at 4.4 days (95%CI: 2.9 6.7) and SD of SI at 3.0 days (95%CI: 1.8 5.8) by using the information of all 21 transmission chains in Hong Kong. Conclusion: The SI of COVID 19 may be shorter than the preliminary estimates in previous works. Given the likelihood that SI could be shorter than the incubation period, pre symptomatic transmission may occur, and extra efforts on timely contact tracing and quarantine are recommended in combating the COVID 19 outbreak.
medRxiv