Implementation and Extended Evaluation of the Euroimmun Anti-SARS-CoV-2 IgG Assay and Its Contribution to the United Kingdom’s COVID-19 Public Health Response

  1. Ashley David Otter
  2. Abbie Bown
  3. Silvia D’Arcangelo
  4. Daniel Bailey
  5. Amanda Semper
  6. Jacqueline Hewson
  7. Matthew Catton
  8. Prem Perumal
  9. Angela Sweed
  10. Deborah Fox McKee
  11. Jessica Jones
  12. Heli Harvala
  13. Abigail Lamikanra
  14. Maria Zambon
  15. Nick Andrews
  16. Heather Whitaker
  17. Ezra Linley
  18. Alexander J. Mentzer
  19. Donal Skelly
  20. Julian C. Knight
  21. Paul Klenerman
  22. UKHSA Porton Euroimmun testing group
  23. Gayatri Amirthalingam
  24. Stephen Taylor
  25. Cathy Rowe
  26. Richard Vipond
  27. Tim Brooks

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Abstract

Serology assays have been useful in determining those with previous SARS-CoV-2 infection in a wide range of research and serosurveillance projects. However, assays vary in their sensitivity at detecting SARS-CoV-2 antibodies. Here, we detail an extended evaluation and characterization of the Euroimmun anti-SARS-CoV-2 IgG assay, one that has been widely used within the United Kingdom on over 160,000 samples.

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  1. Version published to 10.1128/spectrum.02289-21
  2. ScreenIT

    SciScore for 10.1101/2021.10.26.21265497: (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

    Antibodies
    SentencesResources
    Similarly, the NIBSC Anti-SARS-CoV-2 Antibody Diagnostic Calibrant (20/162
    Anti-SARS-CoV-2
    suggested: None

    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04318314RecruitingCOVID-19: Healthcare Worker Bioresource: Immune Protection a…

    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 10.1101/2021.10.26.21265497v1 on medRxiv