Adequacy of Serial Self-performed SARS-CoV-2 Rapid Antigen Detection Testing for Longitudinal Mass Screening in the Workplace

  1. Jesse Papenburg
  2. Jonathon R. Campbell
  3. Chelsea Caya
  4. Cynthia Dion
  5. Rachel Corsini
  6. Matthew P. Cheng
  7. Dick Menzies
  8. Cédric P. Yansouni

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Abstract

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  1. Version published to 10.1001/jamanetworkopen.2022.10559
  2. ScreenIT

    SciScore for 10.1101/2022.02.10.22270805: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: 10 Informed consent was obtained for each participant.
    IRB: The study was approved by the Research Ethics Board of the Research Institute of the McGill University Health Centre (MP-37-2022-7762).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Study data were collected and managed using REDCap.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    Diagnostic testing procedures: The RADT used was the Panbio COVID-19 Ag Rapid Test Device (Abbott Laboratories, Saint-Laurent, Quebec).
    Abbott Laboratories
    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: We detected the following sentences addressing limitations in the study:
    Limitations include the small proportion of eligible businesses that entered the study, and that a single RADT was assessed with uncertain generalizability to the full diversity of available RADTs. Self-administered RADTs are inexpensive and can be decentralised and implemented at scale for serial mass testing of asymptomatic persons to break chains of transmission and reduce SARS-CoV-2 incidence.14,15 This work shows that longitudinal mass SARS-CoV-2 RADT testing can be accurately self-performed and provides evidence for optimizing performance. This use case may become more pertinent with the emergence of new SARS-CoV-2 variants of concern.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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 10.1101/2022.02.10.22270805 on medRxiv