Early phylogenetic estimate of the effective reproduction number of SARS‐CoV‐2
To reconstruct the evolutionary dynamics of the 2019 novel‐coronavirus recently causing an outbreak in Wuhan, China, 52 SARS‐CoV‐2 genomes available on 4 February 2020 at Global Initiative on Sharing All Influenza Data were analyzed. The two models used to estimate the reproduction number (coalescen...
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| Published in | Journal of medical virology Vol. 92; no. 6; pp. 675 - 679 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
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United States
Wiley Subscription Services, Inc
01.06.2020
John Wiley and Sons Inc |
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| Abstract | To reconstruct the evolutionary dynamics of the 2019 novel‐coronavirus recently causing an outbreak in Wuhan, China, 52 SARS‐CoV‐2 genomes available on 4 February 2020 at Global Initiative on Sharing All Influenza Data were analyzed. The two models used to estimate the reproduction number (coalescent‐based exponential growth and a birth‐death skyline method) indicated an estimated mean evolutionary rate of 7.8 × 10−4 subs/site/year (range, 1.1 × 10−4‐15 × 10−4) and a mean tMRCA of the tree root of 73 days. The estimated R value was 2.6 (range, 2.1‐5.1), and increased from 0.8 to 2.4 in December 2019. The estimated mean doubling time of the epidemic was between 3.6 and 4.1 days. This study proves the usefulness of phylogeny in supporting the surveillance of emerging new infections even as the epidemic is growing.
Highlights
The aim of this study was to investigate the temporal origin, rate of viral evolution and population dynamics of SARS‐CoV‐2.
The Bayesian approach used indicated a most probable origin of the epidemic between October and November 2019.
The estimated effective reproductive number increased from 0.8 to 2.4 in December 2019 when the mean doubling time was about 4 days.
This study proves the usefulness of phylogeny in supporting the surveillance of emerging new infections. |
|---|---|
| AbstractList | To reconstruct the evolutionary dynamics of the 2019 novel-coronavirus recently causing an outbreak in Wuhan, China, 52 SARS-CoV-2 genomes available on 4 February 2020 at Global Initiative on Sharing All Influenza Data were analyzed. The two models used to estimate the reproduction number (coalescent-based exponential growth and a birth-death skyline method) indicated an estimated mean evolutionary rate of 7.8 × 10-4 subs/site/year (range, 1.1 × 10-4 -15 × 10-4 ) and a mean tMRCA of the tree root of 73 days. The estimated R value was 2.6 (range, 2.1-5.1), and increased from 0.8 to 2.4 in December 2019. The estimated mean doubling time of the epidemic was between 3.6 and 4.1 days. This study proves the usefulness of phylogeny in supporting the surveillance of emerging new infections even as the epidemic is growing.To reconstruct the evolutionary dynamics of the 2019 novel-coronavirus recently causing an outbreak in Wuhan, China, 52 SARS-CoV-2 genomes available on 4 February 2020 at Global Initiative on Sharing All Influenza Data were analyzed. The two models used to estimate the reproduction number (coalescent-based exponential growth and a birth-death skyline method) indicated an estimated mean evolutionary rate of 7.8 × 10-4 subs/site/year (range, 1.1 × 10-4 -15 × 10-4 ) and a mean tMRCA of the tree root of 73 days. The estimated R value was 2.6 (range, 2.1-5.1), and increased from 0.8 to 2.4 in December 2019. The estimated mean doubling time of the epidemic was between 3.6 and 4.1 days. This study proves the usefulness of phylogeny in supporting the surveillance of emerging new infections even as the epidemic is growing. To reconstruct the evolutionary dynamics of the 2019 novel‐coronavirus recently causing an outbreak in Wuhan, China, 52 SARS‐CoV‐2 genomes available on 4 February 2020 at Global Initiative on Sharing All Influenza Data were analyzed. The two models used to estimate the reproduction number (coalescent‐based exponential growth and a birth‐death skyline method) indicated an estimated mean evolutionary rate of 7.8 × 10−4 subs/site/year (range, 1.1 × 10−4‐15 × 10−4) and a mean tMRCA of the tree root of 73 days. The estimated R value was 2.6 (range, 2.1‐5.1), and increased from 0.8 to 2.4 in December 2019. The estimated mean doubling time of the epidemic was between 3.6 and 4.1 days. This study proves the usefulness of phylogeny in supporting the surveillance of emerging new infections even as the epidemic is growing. Highlights The aim of this study was to investigate the temporal origin, rate of viral evolution and population dynamics of SARS‐CoV‐2. The Bayesian approach used indicated a most probable origin of the epidemic between October and November 2019. The estimated effective reproductive number increased from 0.8 to 2.4 in December 2019 when the mean doubling time was about 4 days. This study proves the usefulness of phylogeny in supporting the surveillance of emerging new infections. To reconstruct the evolutionary dynamics of the 2019 novel-coronavirus recently causing an outbreak in Wuhan, China, 52 SARS-CoV-2 genomes available on 4 February 2020 at Global Initiative on Sharing All Influenza Data were analyzed. The two models used to estimate the reproduction number (coalescent-based exponential growth and a birth-death skyline method) indicated an estimated mean evolutionary rate of 7.8 × 10 subs/site/year (range, 1.1 × 10 -15 × 10 ) and a mean tMRCA of the tree root of 73 days. The estimated R value was 2.6 (range, 2.1-5.1), and increased from 0.8 to 2.4 in December 2019. The estimated mean doubling time of the epidemic was between 3.6 and 4.1 days. This study proves the usefulness of phylogeny in supporting the surveillance of emerging new infections even as the epidemic is growing. To reconstruct the evolutionary dynamics of the 2019 novel‐coronavirus recently causing an outbreak in Wuhan, China, 52 SARS‐CoV‐2 genomes available on 4 February 2020 at Global Initiative on Sharing All Influenza Data were analyzed. The two models used to estimate the reproduction number (coalescent‐based exponential growth and a birth‐death skyline method) indicated an estimated mean evolutionary rate of 7.8 × 10−4 subs/site/year (range, 1.1 × 10−4‐15 × 10−4) and a mean tMRCA of the tree root of 73 days. The estimated R value was 2.6 (range, 2.1‐5.1), and increased from 0.8 to 2.4 in December 2019. The estimated mean doubling time of the epidemic was between 3.6 and 4.1 days. This study proves the usefulness of phylogeny in supporting the surveillance of emerging new infections even as the epidemic is growing. To reconstruct the evolutionary dynamics of the 2019 novel‐coronavirus recently causing an outbreak in Wuhan, China, 52 SARS‐CoV‐2 genomes available on 4 February 2020 at Global Initiative on Sharing All Influenza Data were analyzed. The two models used to estimate the reproduction number (coalescent‐based exponential growth and a birth‐death skyline method) indicated an estimated mean evolutionary rate of 7.8 × 10 −4 subs/site/year (range, 1.1 × 10 −4 ‐15 × 10 −4 ) and a mean tMRCA of the tree root of 73 days. The estimated R value was 2.6 (range, 2.1‐5.1), and increased from 0.8 to 2.4 in December 2019. The estimated mean doubling time of the epidemic was between 3.6 and 4.1 days. This study proves the usefulness of phylogeny in supporting the surveillance of emerging new infections even as the epidemic is growing. The aim of this study was to investigate the temporal origin, rate of viral evolution and population dynamics of SARS‐CoV‐2. The Bayesian approach used indicated a most probable origin of the epidemic between October and November 2019. The estimated effective reproductive number increased from 0.8 to 2.4 in December 2019 when the mean doubling time was about 4 days. This study proves the usefulness of phylogeny in supporting the surveillance of emerging new infections. |
| Author | Bergna, Annalisa Lai, Alessia Galli, Massimo Acciarri, Carla Zehender, Gianguglielmo |
| AuthorAffiliation | 1 Department of Biomedical and Clinical Sciences "L. Sacco" University of Milan Milano Italy 2 Coordinated Research Center "EpiSoMI" University of Milan Milano Italy 3 Romeo ed Enrica Invernizzi Pediatric Research Center University of Milan Milano Italy |
| AuthorAffiliation_xml | – name: 3 Romeo ed Enrica Invernizzi Pediatric Research Center University of Milan Milano Italy – name: 2 Coordinated Research Center "EpiSoMI" University of Milan Milano Italy – name: 1 Department of Biomedical and Clinical Sciences "L. Sacco" University of Milan Milano Italy |
| Author_xml | – sequence: 1 givenname: Alessia orcidid: 0000-0002-3174-5721 surname: Lai fullname: Lai, Alessia organization: University of Milan – sequence: 2 givenname: Annalisa surname: Bergna fullname: Bergna, Annalisa organization: University of Milan – sequence: 3 givenname: Carla surname: Acciarri fullname: Acciarri, Carla organization: University of Milan – sequence: 4 givenname: Massimo orcidid: 0000-0001-8887-6215 surname: Galli fullname: Galli, Massimo organization: University of Milan – sequence: 5 givenname: Gianguglielmo orcidid: 0000-0002-1886-2915 surname: Zehender fullname: Zehender, Gianguglielmo email: gianguglielmo.zehender@unimi.it organization: University of Milan |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32096566$$D View this record in MEDLINE/PubMed |
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| Snippet | To reconstruct the evolutionary dynamics of the 2019 novel‐coronavirus recently causing an outbreak in Wuhan, China, 52 SARS‐CoV‐2 genomes available on 4... To reconstruct the evolutionary dynamics of the 2019 novel-coronavirus recently causing an outbreak in Wuhan, China, 52 SARS-CoV-2 genomes available on 4... |
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| SubjectTerms | Base Sequence Bayes Theorem Bayesian analysis Betacoronavirus - classification Betacoronavirus - genetics Betacoronavirus - isolation & purification Betacoronavirus - pathogenicity Coronavirus Infections - diagnosis Coronavirus Infections - epidemiology Coronavirus Infections - transmission Coronavirus Infections - virology Coronaviruses COVID-19 Epidemics Epidemiological Monitoring Evolution Evolution, Molecular evolutionary dynamics Genome, Viral Genomes Humans Infections Influenza Information Dissemination Mathematical models Models, Statistical Open Reading Frames Pandemics Phylogeny Pneumonia, Viral - diagnosis Pneumonia, Viral - epidemiology Pneumonia, Viral - transmission Pneumonia, Viral - virology Population dynamics Reproduction reproductive number RNA, Viral - genetics SARS-CoV-2 Sequence Alignment Sequence Homology, Nucleic Acid Severe acute respiratory syndrome Severe acute respiratory syndrome coronavirus 2 Short Communication Short Communications Surveillance Viral diseases Virology |
| Title | Early phylogenetic estimate of the effective reproduction number of SARS‐CoV‐2 |
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