Face masks to prevent transmission of COVID-19: A systematic review and meta-analysis

  1. Yanni Li
  2. Mingming Liang
  3. Liang Gao
  4. Mubashir Ayaz Ahmed
  5. John Patrick Uy
  6. Ce Cheng
  7. Qin Zhou
  8. Chenyu Sun

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Abstract

No abstract available

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  1. Version published to 10.1016/j.ajic.2020.12.007
  2. ScreenIT

    SciScore for 10.1101/2020.10.16.20214171: (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

    Software and Algorithms
    SentencesResources
    Regarding this meta-analysis, a comprehensive searching strategy was carefully designed to select eligible studies from multiple electronic databases, including PubMed, Web of Science, Cochrane Library, and Chinese National Knowledge Infrastructure (CNKI), VIP (Chinese) database.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Cochrane Library
    suggested: (Cochrane Library, RRID:SCR_013000)

    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 investigation also had several limitations. First, all the included studies were case-control studies and lacked adequately designed and high-quality randomized controlled studies. This may reduce the overall strength of the results. Second, because more research is currently focused on the treatment and pathology of COVID-19, the total sample size of studies on the effectiveness of PPE is still relatively small. We will continue to focus on the progress of relevant population-based studies. Third, the available studies that provided data for some subgroup analyses were limited, thus the statistical power was relatively low and the results should be interpreted with caution. Fourth, this study performed meta-analysis on the unadjusted and adjusted data to calculate the corresponding results, however, the included original studies did not make the same adjustments for possible confounding factors, such as gender, age, vaccination, hand hygiene, age, gender and cultural difference, and thus, the heterogeneity of the final results may be affected.

    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.
    • Thank you for including a protocol registration statement.

    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 10.1101/2020.10.16.20214171v1 on medRxiv