SARS-CoV-2 transmissibility compared between variants of concern and vaccination status

  1. Liang Wang
  2. Xavier Didelot
  3. Yuhai Bi
  4. George F Gao

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Abstract

Since the start of the SARS-CoV-2 pandemic in late 2019, several variants of concern (VOC) have been reported to have increased transmissibility. In addition, despite the progress of vaccination against SARS-CoV-2 worldwide, all vaccines currently in used are known to protect only partially from infection and onward transmission. We combined phylogenetic analysis with Bayesian inference under an epidemiological model to infer the reproduction number (Rt) and also trace person-to-person transmission. We examined the impact of phylogenetic uncertainty and sampling bias on the estimation. Our result indicated that lineage B had a significantly higher transmissibility than lineage A and contributed to the global pandemic to a large extent. In addition, although the transmissibility of VOCs is higher than other exponentially growing lineages, this difference is not very high. The probability of detecting onward transmission from patients infected with SARS-CoV-2 VOCs who had received at least one dose of vaccine was approximate 1.06% (3/284), which was slightly lower but not statistically significantly different from a probability of 1.21% (10/828) for unvaccinated individuals. In addition to VOCs, exponentially growing lineages in each country should also be account for when tailoring prevention and control strategies. One dose of vaccination could not efficiently prevent the onward transmission of SARS-CoV-2 VOCs. Consequently, nonpharmaceutical interventions (such as wearing masks and social distancing) should still be implemented in each country during the vaccination period.

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  1. Version published to 10.1093/bib/bbab594
  2. ScreenIT

    SciScore for 10.1101/2021.06.25.21259565: (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
    Genomic sequences were aligned using Mafft v7.31017.
    Mafft
    suggested: (MAFFT, RRID:SCR_011811)
    We used jModelTest v2.1.619 to find the best substitution model for each dataset from different countries according to the Bayesian Information Criterion.
    jModelTest
    suggested: (jModelTest, RRID:SCR_015244)
    We then used the Bayesian Markov Chain Monte Carlo (MCMC) approach implemented in BEAST v1.10.421 to derive a dated phylogeny for SARS-CoV-2.
    BEAST
    suggested: (BEAST, RRID:SCR_010228)

    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.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2021.06.25.21259565v1 on medRxiv