Prediction of vaccine efficacy of the Delta variant

  1. Xinhua Chen
  2. Andrew S. Azman
  3. Wanying Lu
  4. Ruijia Sun
  5. Nan Zheng
  6. Shijia Ge
  7. Xiaowei Deng
  8. Juan Yang
  9. Daniel T. Leung
  10. Hongjie Yu

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Abstract

The emergence of SARS-CoV-2 variants have raised concerns over the protective efficacy of the current generation of vaccines, and it remains unclear to what extent, if any, different variants impact the efficacy and effectiveness of various SARS-CoV-2 vaccines. We systematically searched for studies of SARS-CoV-2 vaccine efficacy and effectiveness, as well as neutralization data for variants, and used a previously published statistical model to predict vaccine efficacy against variants. Overall, we estimate the efficacy of mRNA-1273 and ChAdOx1 nCoV-19 against infection caused by the Delta variant to be 25-50% lower than that of prototype strains. The predicted efficacy against symptomatic illness of the mRNA vaccines BNT162b2 and mRNA-1273 are 95.1% (UI: 88.4-98.1%) and 80.8% (60.7-92.3%), respectively, which are higher than that of adenovirus-vector vaccines Ad26.COV2.S (44.8%, UI: 29.8-60.1%) and ChAdOx1 nCoV-19 (41.1%, 19.8-62.8%). Taken together, these results suggest that the development of more effective vaccine strategies against the Delta variant may be needed. Finally, the use of neutralizing antibody titers to predict efficacy against variants provides an additional tool for public health decision making, as new variants continue to emerge.

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    SciScore for 10.1101/2021.08.26.21262699: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

    About SciScore

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  2. Version published to 10.1101/2021.08.26.21262699v1 on medRxiv