Spread dynamics of SARS-CoV-2 epidemic in China: a phylogenetic analysis

  1. Hong GuoHu
  2. Guan Qing
  3. Mao Qing

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

Background

Since December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic and infected millions of people. As the first country proclaimed the SARS-CoV-2 outbreak, China implemented travel ban measure, and curbed the epidemic quickly. We performed a phylogenetic analysis to reveal the spread dynamics detail of SARS-CoV-2 in China and the impact of travel ban on SARS-CoV-2.

Method

Focusing on SARS-CoV-2 sequences collected from China in public database released as of March 31, 2020, we performed a Bayesian inference phylogenetic analyses to estimate the effective population size ( Ne ) curve of SARS-CoV-2 epidemic. Furthermore, we displayed the geographic spread mode of SARS-CoV-2 among different China regions by using Bayesian stochastic search variable selection (BSSVS) method.

Results

The most recent common ancestor (tMRCA) of SARS-CoV-2 in China was traced back to December 9, 2019. According the Ne estimation and geographic spread reconstruction, January 25, 2020 was considered as the crucial time point during the SARS-CoV-2 epidemic in China,which was 2 days after the travel ban implemented. On the point, the tendency of viral population size changed from ascending to decreasing, and the cross-regional spread paths were blocked.

Conclusions

Travel ban is an effective measure to intervene in the spread of SARS-CoV-2, It is necessary to continue efforts in research for prevention and control measures.

Article activity feed

  1. Version published to 10.1101/2020.05.20.20107854v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.05.20.20107854: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    A multiple alignment was performed by CLUSTAL X program(7) and trimmed into full-length S gene with 3822nt.
    CLUSTAL X
    suggested: (Clustal X , RRID:SCR_017055)
    General Time Reversible (GTR) was selected as the nucleotide substitution model by calculated AIC score using jModeltest v1.9.1 program(10).
    jModeltest
    suggested: (jModelTest, RRID:SCR_015244)
    The output files generated by bayesian computing were discarded the first 10% as burn-in and then combined by LogCombiner tool in BEAST v1.10.4 packages.
    BEAST
    suggested: (BEAST, RRID:SCR_010228)
    Tracer software v1.7.1(17) was used to diagnose MCMCs output and estimate Ne curve with additional 10% burn-in.
    Tracer
    suggested: (Tracer, RRID:SCR_019121)
    We displayed the discrete geographical phylogenetic MCC trees in FigTree v1.4.3 and generated a visual kml file by spreaD3 v0.9.7(19), which was viewed in Google Earth v7.1.8.
    FigTree
    suggested: (FigTree, RRID:SCR_008515)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.05.20.20107854v1 on medRxiv