Inference of person-to-person transmission of COVID-19 reveals hidden super-spreading events during the early outbreak phase

Liang Wang, Xavier Didelot, Jing Yang, Gary Wong, Yi Shi, Wenjun Liu, George F. Gao and Yuhai Bi ()
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Liang Wang: Chinese Academy of Sciences
Xavier Didelot: University of Warwick
Jing Yang: Chinese Academy of Sciences
Gary Wong: Institut Pasteur of Shanghai, Chinese Academy of Sciences
Yi Shi: Chinese Academy of Sciences
Wenjun Liu: Chinese Academy of Sciences
George F. Gao: Chinese Academy of Sciences
Yuhai Bi: Chinese Academy of Sciences

Nature Communications, 2020, vol. 11, issue 1, 1-6

Abstract: Abstract Coronavirus disease 2019 (COVID-19) was first identified in late 2019 in Wuhan, Hubei Province, China and spread globally in months, sparking worldwide concern. However, it is unclear whether super-spreading events occurred during the early outbreak phase, as has been observed for other emerging viruses. Here, we analyse 208 publicly available SARS-CoV-2 genome sequences collected during the early outbreak phase. We combine phylogenetic analysis with Bayesian inference under an epidemiological model to trace person-to-person transmission. The dispersion parameter of the offspring distribution in the inferred transmission chain was estimated to be 0.23 (95% CI: 0.13–0.38), indicating there are individuals who directly infected a disproportionately large number of people. Our results showed that super-spreading events played an important role in the early stage of the COVID-19 outbreak.

Date: 2020
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DOI: 10.1038/s41467-020-18836-4

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