Predictors of self-reported symptoms and testing for COVID-19 in Canada using a nationally representative survey

  1. Daphne C. Wu
  2. Prabhat Jha
  3. Teresa Lam
  4. Patrick Brown
  5. Hellen Gelband
  6. Nico Nagelkerke
  7. H. Chaim Birnboim
  8. Angus Reid
  9. on behalf of the Action to Beat Coronavirus in Canada/Action pour Battre le Coronavirus (Ab-C) Study Group

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Abstract

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  1. Version published to 10.1371/journal.pone.0240778
  2. ScreenIT

    SciScore for 10.1101/2020.05.29.20109090: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Ethics approval: The Angus Reid Forum obtains consent from all participants, and the polling data without any individual identifiers are made available openly to bona-fide researchers.
    IRB: Ethics approval was not required as per Unity Health Toronto Research Ethics Board.
    RandomizationThe Angus Reid Institute (ARI) conducted an online survey from April 1-5, 2020, among a representative randomized sample of 4,240 Canadian adults who are members of Angus Reid Forum, a national online sample of 50,000 Canadians used for political and other social polling (Angus Reid Institute, 2020).
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We used RStudio Version 1.1.453 for analyses.
    RStudio
    suggested: (RStudio, RRID:SCR_000432)

    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:
    There are surprisingly few nationally representative studies, and despite some limitations, this study represents the first to document self-reported symptoms in a reasonably representative sample. COVID symptoms overlap with some other infections, notably seasonal influenza, which could have inflated the coronavirus rates in this survey. However, a study comparing the COVID symptom syndrome with other infections in the United States suggests that most are actually due to COVID (Centers for Disease Control and Prevention, 2020). We found possible COVID symptoms to be less prevalent and the levels of testing marginally less prevalent in older adults than other age groups, despite the certainty that the vast majority of COVID hospitalizations and deaths occur at older ages. However, a weakness of our sample is the lack of representation from nursing and long-term care residents, in whom more than three-quarters of all COVID deaths occur (Eggertson and Wolfville, 2020). There may be additional reasons for the age-specific findings, however. Anecdotal reports suggest that older adults do not experience the symptoms used to define COVID infection in the poll, but may report vaguer symptoms such as dizziness and confusion (Graham, 2020). Further surveys focused on syndromes that might occur in older adults are warranted. The testing results are broadly consistent with reports of the general levels of access to SARS-CoV-2 testing during the survey time period, including a higher lev...

    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 10.1101/2020.05.29.20109090v1 on medRxiv