SARS-CoV-2 Seroprevalence in Relation to Timing of Symptoms

  1. Joseph E. Ebinger
  2. Gregory J. Botwin
  3. Christine M. Albert
  4. Mona Alotaibi
  5. Moshe Arditi
  6. Anders H. Berg
  7. Aleksandra Binek
  8. Patrick Botting
  9. Justyna Fert-Bober
  10. Jane C. Figueiredo
  11. Jonathan D. Grein
  12. Wohaib Hasan
  13. Mir Henglin
  14. Shehnaz K. Hussain
  15. Mohit Jain
  16. Sandy Joung
  17. Michael Karin
  18. Elizabeth H. Kim
  19. Dalin Li
  20. Yunxian Liu
  21. Eric Luong
  22. Dermot P.B. McGovern
  23. Akil Merchant
  24. Noah Merin
  25. Peggy B. Miles
  26. Trevor-Trung Nguyen
  27. Koen Raedschelders
  28. Mohamad A. Rashid
  29. Celine E. Riera
  30. Richard V. Riggs
  31. Sonia Sharma
  32. Kimia Sobhani
  33. Sarah Sternbach
  34. Nancy Sun
  35. Warren G. Tourtellotte
  36. Jennifer E. Van Eyk
  37. Jonathan G. Braun
  38. Susan Cheng

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Abstract

Of individuals with SARS-CoV-2 IgG antibody testing performed, those who contemporaneously experienced a cluster of Covid-19 relevant symptoms in the 1-2 months preceding the antibody assay were more likely to test positive whereas those who experienced the symptom clustering in the prior 3-6 months were more likely to test negative. These findings suggest that antibodies likely wane over a period of months, particularly in relation to the timing of symptoms.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.02.20166876: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Based on emerging data, the following 4 symptoms were considered most relevant to Covid-19: anosmia, fever, dry cough, and myalgias.8,9 All study protocols were approved by the Cedars Sinai institutional review board and all participants provided written informed consent.
    Consent: Based on emerging data, the following 4 symptoms were considered most relevant to Covid-19: anosmia, fever, dry cough, and myalgias.8,9 All study protocols were approved by the Cedars Sinai institutional review board and all participants provided written informed consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    All participants were invited to receive SARS-CoV-2 IgG antibody testing (Abbott Architect7) in addition to completing an electronic survey of questions regarding Covid-19 related symptoms.
    SARS-CoV-2 IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    All participants were invited to receive SARS-CoV-2 IgG antibody testing (Abbott Architect7) in addition to completing an electronic survey of questions regarding Covid-19 related symptoms.
    Abbott
    suggested: (Abbott, RRID:SCR_010477)

    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: We detected the following sentences addressing limitations in the study:
    We attempted to control for this limitation by focusing on symptom clustering that is more specific to Covid-19, including anosmia. Further investigations are needed to validate our results and also examine the extent to which antibody persistence or lack thereof may or may not represent time-dependent variation in relative immunity to Covid-19. Overall, our study findings offer important context for clinicians, scientists, and public health officials as part of ongoing efforts to deploy and interpreting results of antibody testing in populations at large.

    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

    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.

  2. Version published to 10.1101/2020.08.02.20166876v1 on medRxiv