Predominance of antibody-resistant SARS-CoV-2 variants in vaccine breakthrough cases from the San Francisco Bay Area, California

  1. Venice Servellita
  2. Mary Kate Morris
  3. Alicia Sotomayor-Gonzalez
  4. Amelia S. Gliwa
  5. Erika Torres
  6. Noah Brazer
  7. Alicia Zhou
  8. Katherine T. Hernandez
  9. Madeline Sankaran
  10. Baolin Wang
  11. Daniel Wong
  12. Candace Wang
  13. Yueyuan Zhang
  14. Kevin R. Reyes
  15. Dustin Glasner
  16. Xianding Deng
  17. Jessica Streithorst
  18. Steve Miller
  19. Edwin Frias
  20. Mary Rodgers
  21. Gavin Cloherty
  22. John Hackett
  23. Carl Hanson
  24. Debra Wadford
  25. Susan Philip
  26. Scott Topper
  27. Darpun Sachdev
  28. Charles Y. Chiu

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Abstract

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  1. Version published to 10.1038/s41564-021-01041-4
  2. ScreenIT

    SciScore for 10.1101/2021.08.19.21262139: (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

    Software and Algorithms
    SentencesResources
    Raw sequence data were submitted to the Sequence Read Archive (SRA) database.
    Sequence Read Archive
    suggested: (DDBJ Sequence Read Archive, RRID:SCR_001370)
    (BioProject accession number PRJNA722044 and umbrella BioProject accession number PRJNA171119).
    BioProject
    suggested: (NCBI BioProject, RRID:SCR_004801)
    Code Availability: FASTA files and scripting code for data analyses are available in a Zenodo data repository (https://doi.org/10.5281/zenodo.5207242).
    Zenodo
    suggested: (ZENODO, RRID:SCR_004129)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are several limitations to our study. First, breakthrough infections in this study were identified by testing of persons presenting to a tertiary hospital and associated clinics or as part of community-based testing by a commercial laboratory, so sampling bias may be present. This limitation is mitigated by our results showing similar variant distributions and viral load comparisons across two separate test cohorts. Second, the total number of vaccinated persons with breakthrough infections was relatively small at 125, of which clinical and epidemiologic metadata were only available for 39. Third, clinical data were obtained by retrospective medical chart review, and some of the data were incomplete or may have been subject to inaccurate reporting. Fourth, in the absence of contact tracing metadata, we were unable to assess transmission and secondary attack rates from vaccinated persons to exposed contacts. In summary, our results reveal that selection pressure in a highly vaccinated community (>71% fully vaccinated as of early August 2021) favors more infectious, antibody-resistant VOCs such as the gamma12,32 and delta12,13,21,25 variants, and that high-titer symptomatic post-vaccination infections may be a contributor to viral spread. Concerns have also been raised regarding waning immunity resulting in decreased effectiveness of the vaccine in preventing symptomatic infection over time33. Combined with other potential factors such as relaxation of COVID-19 restrictio...

    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.

    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 10.1101/2021.08.19.21262139 on medRxiv