Effects of New York’s Executive Order on Face Mask Use on COVID-19 Infections and Mortality: A Modeling Study

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Abstract

No abstract available

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  1. SciScore for 10.1101/2020.10.26.20219527: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All analyses and simulations were performed in MATLAB R 2019b.
    MATLAB
    suggested: (MATLAB, RRID:SCR_001622)

    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:
    Our study has several limitations and practical simplifying assumptions. First, we assumed a homogenous use of face masks among the general population. In reality, people with symptoms are more likely to wear a face mask, whereas people with no symptoms are less likely to wear a face mask. Second, the model did not identify people who are specifically at high-risk, such as people living in a population-dense area and people who are in close contact with infected individuals. Third, we did not model COVID-19 infections and deaths across different racial/ethnic groups due to the lack of such granular data over the study period. Lastly, the effectiveness of face mask varies considerably across different types of masks. To account for parameter uncertainty, we estimated the effectiveness of face mask based on a most recent meta-analysis and performed sensitivity analyses on the key model parameters.12

    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.