Effect of Timing of and Adherence to Social Distancing Measures on COVID-19 Burden in the United States

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Abstract

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  1. SciScore for 10.1101/2020.06.07.20124859: (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

    No key resources detected.


    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 limitations, most of which are due to limited available data and uncertainty regarding SARS-CoV-2. We make simplifying assumptions such as asymptomatic patients transmit the disease at the same rate as symptomatic patients and weather does not affect SARS-CoV-2 transmissibility whereas several studies suggest otherwise.26,27 Furthermore, COVAM uses adherence to social distancing as a proxy for several factors contributing to the disease transmission including fewer close contacts due to limited travel and precautions that prevent transmission during a close contact such as wearing masks, therefore COVAM may not be accurately estimating the impact of personal precautions on transmission. To overcome this limitation, we assumed a high level of adherence after the easing of social distancing measures to provide a conservative estimate on the effect of easing social distancing measures. There are also several limitations related to the modeling approach. Our calibration procedure used a simple trial-error approach as opposed to a full-scale calibration in which all possible combinations of the input parameter values within a plausible range are tested.28 Due to the computational intensity of a more formal and detailed calibration procedure, our calibration process may have not identified the best parameter combinations to represent the pandemic. Additionally, we used mean parameter estimates instead of probability distributions for input parameters to reduce computa...

    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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