Detection of SARS-CoV-2 Antibodies in Oral Fluid Obtained Using a Rapid Collection Device

  1. Melanie A. MacMullan
  2. Prithivi Chellamuthu
  3. Aubree Mades
  4. Sudipta Das
  5. Fred Turner
  6. Vladimir I. Slepnev
  7. Albina Ibrayeva

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Abstract

Current commercially available methods for reliably detecting antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain expensive and inaccessible due to the need for whole-blood collection by highly trained phlebotomists using personal protective equipment (PPE). We have evaluated an antibody detection approach using the OraSure Technologies oral antibody collection device (OACD) and their proprietary SARS-CoV-2 total antibody detection enzyme-linked immunosorbent assay (ELISA).

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  1. Version published to 10.1128/jcm.02510-20
  2. ScreenIT

    SciScore for 10.1101/2020.10.12.20210609: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Oral Fluid ELISA: OraSure® Technologies Anti-SARS-CoV-2 Total Antibody ELISA for oral fluid specimen (item number 3001-3317-70, catalog #1125SB
    Anti-SARS-CoV-2
    suggested: None
    Software and Algorithms
    SentencesResources
    Statistical analysis: ROC curves were generated in GraphPad Prism (GraphPad Prism Version 8.4.3, San Diego, USA), with a 95% confidence interval.
    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: We detected the following sentences addressing limitations in the study:
    This antibody detection system allows us to overcome the limitations presented by currently administered serum antibody tests, increasing accessibility to antibody testing and enabling a better understanding of the trends of immune response against this virus over time.

    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.

  3. Version published to 10.1101/2020.10.12.20210609 on medRxiv