Reliable estimation of SARS-CoV-2 anti-spike protein IgG titers from single dilution optical density values in serologic surveys

  1. Emilia M.M. Andrade Belitardo
  2. Nivison Nery
  3. Juan P. Aguilar Ticona
  4. Moyra Machado Portilho
  5. Iago O. Mello
  6. Guilherme S. Ribeiro
  7. Mitermayer G. Reis
  8. Federico Costa
  9. Derek A.T. Cummings
  10. Albert I. Ko
  11. Mariam O. Fofana

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Abstract

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  1. Version published to 10.1016/j.diagmicrobio.2022.115807
  2. ScreenIT

    SciScore for 10.1101/2022.02.13.22270904: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Individuals who sleep 3 or more nights per week within the defined study area, are aged 2 years or older, and who provide consent (parental consent for minors) were eligible to participate.
    IRB: This project was approved by the Human Research Ethics Committee of the Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (FIOCRUZ), the National Research Ethics Council (CONEP) and the Yale University Research Ethics Committee.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Threshold for antibody detection: For the Euroimmun anti-S IgG ELISA, the manufacturer recommends that samples with normalized OD values <0.8 are considered negative, those with values >=0.8 and <1.1 considered borderline, and those with values >=1.1 considered positive.
    IgG ELISA
    suggested: None
    Software and Algorithms
    SentencesResources
    Interpolated titers were computed using the software GraphPad Prism (Version 5.01, GraphPad software, San Diego, USA).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.

    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 10.1101/2022.02.13.22270904v1 on medRxiv