4.2 Article

Estimating the generation interval and inferring the latent period of COVID-19 from the contact tracing data

Journal

EPIDEMICS
Volume 36, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.epidem.2021.100482

Keywords

COVID-19; Generation interval; Latent period; Serial interval; Incubation period; Contact tracing; Statistical inference

Funding

  1. Alibaba (China) Co. Ltd.
  2. Research Grants Council (RGC) of Hong Kong, China [15205119]

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This study estimated the generation interval and incubation period of COVID-19 using contact tracing data, finding that approximately half of the secondary infections may be due to pre-symptomatic transmission, emphasizing the importance of isolation for both symptomatic and pre-symptomatic cases.
The coronavirus disease 2019 (COVID-19) emerged by end of 2019, and became a serious public health threat globally in less than half a year. The generation interval and latent period, though both are of importance in understanding the features of COVID-19 transmission, are difficult to observe, and thus they can rarely be learnt from surveillance data empirically. In this study, we develop a likelihood framework to estimate the generation interval and incubation period simultaneously by using the contact tracing data of COVID-19 cases, and infer the pre-symptomatic transmission proportion and latent period thereafter. We estimate the mean of incubation period at 6.8 days (95 %CI: 6.2, 7.5) and SD at 4.1 days (95 %CI: 3.7, 4.8), and the mean of generation interval at 6.7 days (95 %CI: 5.4, 7.6) and SD at 1.8 days (95 %CI: 0.3, 3.8). The basic reproduction number is estimated ranging from 1.9 to 3.6, and there are 49.8 % (95 %CI: 33.3, 71.5) of the secondary COVID-19 infections likely due to pre-symptomatic transmission. Using the best estimates of model parameters, we further infer the mean latent period at 3.3 days (95 %CI: 0.2, 7.9). Our findings highlight the importance of both isolation for symptomatic cases, and for the pre-symptomatic and asymptomatic cases.

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