Mask-wearing and control of SARS-CoV-2 transmission in the USA: a cross-sectional study

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Abstract

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  1. SciScore for 10.1101/2020.08.23.20078964: (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
    Duration of time spent at home was estimated with the Google community “residential time” mobility measure23, which was estimated using anonymized and aggregated data from individual Google users who opted into location history on their mobile devices24.
    Google
    suggested: (Google, RRID:SCR_017097)

    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:
    A state that demonstrates social distancing may also be subject to additional non-modeled but impactful interventions including gathering size reductions, travel limitations, and the closing of businesses38. While the social distancing proxy used here captures the broad activity level that would result from the implementation of these policies, future research should focus on incorporating data from disaggregated interventions with empirical assessments of mask wearing. Additionally, potential Rt and mask wearing within a state may be the result of prior transmission. While we showed the effect of mask wearing was robust to peak Rt in the first wave of the epidemic, our methods do not control for time-dependent confounding or variations in mask usage by susceptibility status. The validity of epidemiologic parameters of transmission are only as accurate as the incidence data to which the models are fit. If states reporting low mask wearing also underreport incidence (e.g. limited testing), we may be underestimating the true effect of mask wearing. Conversely, instantaneous Rt estimations of transmission are subject to uncertainty, especially towards the end of the time-series before reports are complete27. While our results were robust to different estimators, our model does not account for estimation error. Additionally, mask wearing measures, social distancing and Rt all exhibit significant temporal autocorrelation. To combat this, we dichotomized Rt and aggregated our expos...

    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

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