Genomic epidemiology of the early stages of the SARS-CoV-2 outbreak in Russia

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Abstract

The ongoing pandemic of SARS-CoV-2 presents novel challenges and opportunities for the use of phylogenetics to understand and control its spread. Here, we analyze the emergence of SARS-CoV-2 in Russia in March and April 2020. Combining phylogeographic analysis with travel history data, we estimate that the sampled viral diversity has originated from at least 67 closely timed introductions into Russia, mostly in late February to early March. All but one of these introductions were not from China, suggesting that border closure with China has helped delay establishment of SARS-CoV-2 in Russia. These introductions resulted in at least 9 distinct Russian lineages corresponding to domestic transmission. A notable transmission cluster corresponded to a nosocomial outbreak at the Vreden hospital in Saint Petersburg; phylodynamic analysis of this cluster reveals multiple (2-3) introductions each giving rise to a large number of cases, with a high initial effective reproduction number of 3.0 [1.9, 4.3].

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  1. SciScore for 10.1101/2020.07.14.20150979: (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

    Experimental Models: Cell Lines
    SentencesResources
    Virus isolation: For some of the SARS-CoV-2 PCR-positive samples (see Supplementary Data 2), viruses were isolated in Vero cell culture (ATCC #CCL-81).
    Vero
    suggested: ATCC Cat# CCL-81, RRID:CVCL_0059)
    Software and Algorithms
    SentencesResources
    MinION (Oxford Nanopore) (flow cell R9.4.1) was used for whole-genome sequencing.
    MinION
    suggested: (MinION, RRID:SCR_017985)
    Basecalled reads were processed by Porechop 68 in two steps.
    Porechop
    suggested: (Porechop, RRID:SCR_016967)
    The obtained sequences were aligned with MAFFT 7.453 73 with the following parameters: ‘ --addfragments --keeplength’.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    The final alignment was used to construct the phylogenetic tree with IQ-Tree 1.6.12 74 with GTR substitution model and ‘-fast’ option.
    IQ-Tree
    suggested: (IQ-TREE, RRID:SCR_017254)
    To address the bias in collection dates, we used the symptoms onset date instead of the collection date in BEAST2 analysis, estimating it as follows.
    BEAST2
    suggested: (BEAST2, RRID:SCR_017307)
    Maps were visualized with the ggplot2 package in R.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Phylogenetic trees were visualized with the ETE3 toolkit 78 in Python 3 and iTOL v4 79.
    Python
    suggested: (IPython, RRID:SCR_001658)
    The maximum clade credibility tree was visualized with FigTree 80.
    FigTree
    suggested: (FigTree, RRID:SCR_008515)

    Results from OddPub: Thank you for sharing your data.


    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

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