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Phylogenetic and phylodynamic analyses of SARS-CoV-2.
- Source :
-
Virus Research . Oct2020, Vol. 287, pN.PAG-N.PAG. 1p. - Publication Year :
- 2020
-
Abstract
- • We estimated the time to the most recent common ancestor (TMRCA) and evolutionary rate of SARS-CoV-2 to be 12 November 2019 (95% BCI: 11 October 2019 and 09 December 2019) and 9.90 × 10-4 substitutions per site per year (95% BCI: 6.29 × 10-4–1.35 × 10-3), respectively. • Our results emphasize the importance of using phylogenetic and phylodynamic analyses to provide insights into the roles of various interventions to limit the spread of SARS-CoV-2 in China and beyond. • Understanding epidemic dynamics of SARS-CoV-2 in real time is increasingly important for guiding prevention efforts. To investigate the evolutionary and epidemiological dynamics of the current COVID-19 outbreak, a total of 112 genomes of SARS-CoV-2 strains sampled from China and 12 other countries with sampling dates between 24 December 2019 and 9 February 2020 were analyzed. We performed phylogenetic, split network, likelihood-mapping, model comparison, and phylodynamic analyses of the genomes. Based on Bayesian time-scaled phylogenetic analysis with the best-fitting combination models, we estimated the time to the most recent common ancestor (TMRCA) and evolutionary rate of SARS-CoV-2 to be 12 November 2019 (95 % BCI: 11 October 2019 and 09 December 2019) and 9.90 × 10−4 substitutions per site per year (95 % BCI: 6.29 × 10−4–1.35 × 10−3), respectively. Notably, the very low R e estimates of SARS-CoV-2 during the recent sampling period may be the result of the successful control of the pandemic in China due to extreme societal lockdown efforts. Our results emphasize the importance of using phylodynamic analyses to provide insights into the roles of various interventions to limit the spread of SARS-CoV-2 in China and beyond. [ABSTRACT FROM AUTHOR]
- Subjects :
- *SARS-CoV-2
*COVID-19 pandemic
*PANDEMICS
*COVID-19
Subjects
Details
- Language :
- English
- ISSN :
- 01681702
- Volume :
- 287
- Database :
- Academic Search Index
- Journal :
- Virus Research
- Publication Type :
- Academic Journal
- Accession number :
- 145439545
- Full Text :
- https://doi.org/10.1016/j.virusres.2020.198098