Transmission dynamics and evolutionary history of 2019-nCoV.
Identifieur interne : 000205 ( Main/Exploration ); précédent : 000204; suivant : 000206Transmission dynamics and evolutionary history of 2019-nCoV.
Auteurs : Xingguang Li [République populaire de Chine] ; Wei Wang [République populaire de Chine] ; Xiaofang Zhao [République populaire de Chine] ; Junjie Zai [République populaire de Chine] ; Qiang Zhao [République populaire de Chine] ; Yi Li [République populaire de Chine] ; Antoine Chaillon [États-Unis]Source :
- Journal of medical virology [ 1096-9071 ] ; 2020.
Descripteurs français
- KwdFr :
- Chine, Flambées de maladies, Fonctions de vraisemblance, Génome viral, Humains, Infections à coronavirus (transmission), Infections à coronavirus (épidémiologie), Modèles génétiques, Phylogénie, Pneumopathie virale (transmission), Pneumopathie virale (épidémiologie), Taux de mutation, Thaïlande, Théorème de Bayes, États-Unis d'Amérique.
- MESH :
- Wicri :
- geographic : République populaire de Chine, Thaïlande, États-Unis.
English descriptors
- KwdEn :
- Bayes Theorem, Betacoronavirus (genetics), China, Coronavirus Infections (epidemiology), Coronavirus Infections (transmission), Disease Outbreaks, Genome, Viral, Humans, Likelihood Functions, Models, Genetic, Mutation Rate, Phylogeny, Pneumonia, Viral (epidemiology), Pneumonia, Viral (transmission), Thailand, United States.
- MESH :
- geographic : China, Thailand, United States.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- genetics : Betacoronavirus.
- transmission : Coronavirus Infections, Pneumonia, Viral.
- Bayes Theorem, Disease Outbreaks, Genome, Viral, Humans, Likelihood Functions, Models, Genetic, Mutation Rate, Phylogeny.
Abstract
To investigate the time origin, genetic diversity, and transmission dynamics of the recent 2019-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 likelihood-mapping analyses of the genome sequences were performed. On the basis of the likelihood-mapping analysis, the increasing tree-like signals (from 0% to 8.2%, 18.2%, and 25.4%) over time may be indicative of increasing genetic diversity of 2019-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 2019-nCoV strains. The estimated mean evolutionary rate for 2019-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 2019-nCOV transmission in real-time.
DOI: 10.1002/jmv.25701
PubMed: 32027035
Affiliations:
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Chine</term><term>Thaïlande</term><term>États-Unis</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">To investigate the time origin, genetic diversity, and transmission dynamics of the recent 2019-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 likelihood-mapping analyses of the genome sequences were performed. On the basis of the likelihood-mapping analysis, the increasing tree-like signals (from 0% to 8.2%, 18.2%, and 25.4%) over time may be indicative of increasing genetic diversity of 2019-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 2019-nCoV strains. The estimated mean evolutionary rate for 2019-nCoV ranged from 1.7926 × 10<sup>-3</sup> to 1.8266 × 10<sup>-3</sup> 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 2019-nCOV transmission in real-time.</div></front></TEI><affiliations><list><country><li>République populaire de Chine</li><li>États-Unis</li></country><region><li>Californie</li><li>Hubei</li></region><settlement><li>Tianjin</li><li>Wuhan</li></settlement></list><tree><country name="République populaire de Chine"><region name="Hubei"><name sortKey="Li, Xingguang" sort="Li, Xingguang" uniqKey="Li X" first="Xingguang" last="Li">Xingguang Li</name></region><name sortKey="Li, Yi" sort="Li, Yi" uniqKey="Li Y" first="Yi" last="Li">Yi Li</name><name sortKey="Wang, Wei" sort="Wang, Wei" uniqKey="Wang W" first="Wei" last="Wang">Wei Wang</name><name sortKey="Zai, Junjie" sort="Zai, Junjie" uniqKey="Zai J" first="Junjie" last="Zai">Junjie Zai</name><name sortKey="Zhao, Qiang" sort="Zhao, Qiang" uniqKey="Zhao Q" first="Qiang" last="Zhao">Qiang Zhao</name><name sortKey="Zhao, Xiaofang" sort="Zhao, Xiaofang" uniqKey="Zhao X" first="Xiaofang" last="Zhao">Xiaofang Zhao</name></country><country name="États-Unis"><region name="Californie"><name sortKey="Chaillon, Antoine" sort="Chaillon, Antoine" uniqKey="Chaillon A" first="Antoine" last="Chaillon">Antoine Chaillon</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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