Author: Li, Xingguang; Wang, Wei; Zhao, Xiaofang; Zai, Junjie; Zhao, Qiang; Li, Yi; Chaillon, Antoine
Title: Transmission dynamics and evolutionary history of 2019â€nCoV Cord-id: afek8kgr Document date: 2020_2_14
ID: afek8kgr
Snippet: To investigate the time origin, genetic diversity, and transmission dynamics of the recent 2019â€nCoV outbreak in China and beyond, a total of 32 genomes of virus strains sampled from China, Thailand, and the USA with sampling dates between 24 December 2019 and 23 January 2020 were analyzed. Phylogenetic, transmission network, and likelihoodâ€mapping analyses of the genome sequences were performed. On the basis of the likelihoodâ€mapping analysis, the increasing treeâ€like signals (from 0% t
Document: To investigate the time origin, genetic diversity, and transmission dynamics of the recent 2019â€nCoV outbreak in China and beyond, a total of 32 genomes of virus strains sampled from China, Thailand, and the USA with sampling dates between 24 December 2019 and 23 January 2020 were analyzed. Phylogenetic, transmission network, and likelihoodâ€mapping analyses of the genome sequences were performed. On the basis of the likelihoodâ€mapping analysis, the increasing treeâ€like signals (from 0% to 8.2%, 18.2%, and 25.4%) over time may be indicative of increasing genetic diversity of 2019â€nCoV in human hosts. We identified three phylogenetic clusters using the Bayesian inference framework and three transmission clusters using transmission network analysis, with only one cluster identified by both methods using the above genome sequences of 2019â€nCoV strains. The estimated mean evolutionary rate for 2019â€nCoV ranged from 1.7926 × 10(−3) to 1.8266 × 10(−3) substitutions per site per year. On the basis of our study, undertaking epidemiological investigations and genomic data surveillance could positively impact public health in terms of guiding prevention efforts to reduce 2019â€nCOV transmission in realâ€time.
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