Social distancing causally impacts the spread of SARS-CoV-2: a U.S. nationwide event study

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Abstract

We assess the causal impact of social distancing on the spread of SARS-CoV-2 in the U.S. using the quasi-natural experimental setting created by the spontaneous relaxation of social distancing behavior brought on by the protests that erupted across the nation following George Floyd’s tragic death on May 25, 2020. Using a difference-in-difference specification and a balanced sample covering the [− 30, 30] day event window centered on the onset of protests, we document an increase of 1.34 cases per day, per 100,000 population, in the SARS-CoV-2 incidence rate in protest counties, relative to their propensity score matching non-protest counterparts. This represents a 26.8% increase in the incidence rate relative to the week preceding the protests. We find that the treatment effect only manifests itself after the onset of the protests and our placebo tests rule out the possibility that our findings are attributable to chance. Our research informs policy makers and provides insights regarding the usefulness of social distancing as an intervention to minimize the spread of SARS-CoV-2.

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  1. SciScore for 10.1101/2020.06.29.20143131: (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
    Our starting point is the List of George Floyd protests in the United States assembled by Wikipedia.
    Wikipedia
    suggested: (Wikipedia, RRID:SCR_004897)
    In all our regressions, we cluster the standard errors at the county level to account for any potential cross-sectional dependence in the error terms, Ei,j,t.17 We perform our statistical analysis with STATA 16 and use Sergio Correia’s REGHDFE command to estimate equation (1).18 2.3 Research Setting: Two key requirements for the identification of the causal link between social distancing and the spread of SARS-CoV-2 are satisfied in our research setting, namely: 1) the existence of a strong theoretical basis supporting the relationship in question and, 2) exogenous variation in the variable of interest, i.e social distancing.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: Thank you for sharing your code and data.


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and Weaknesses: Early predictive models assessing the effectiveness of social distancing have suggested that a greater spread of SARS-CoV-2 would occur in the absence of social distancing measures.25–27 Similarly, our study demonstrates that when social distancing is reduced, i.e by individuals protesting in close proximity, the spread of SARS-CoV-2 increases. Our study differs from its predecessors because instead of examining the effectiveness of social distancing measures following their imposition, 11,12,14 we examine the impact of social distancing on the spread of COVID-19 when social distancing practices are abruptly relaxed. Additionally, unlike previous studies, we do not use mobility as a measure of social distancing, instead we control for social mobility as a variable in our analyses. By explicitly controlling for the concurrent increase in social mobility and the relaxation of state-imposed social distancing restrictions during the period surrounding the protests, our study demonstrates that social distancing directly impacts the spread of SARS-CoV-2. We also control for a host of covariates known to influence the transmission of SARS-CoV-2, and implement placebo tests to rule out the possibility that our results are attributable to chance. Therefore, we can be confident that the increase in SARS-CoV-2 infections that we observe following the onset of the protests can be attributed to the relaxation of social distancing practices. Our study is not witho...

    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.

  2. SciScore for 10.1101/2020.06.29.20143131: (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
    Our starting point is the List of George Floyd protests in the United States assembled by Wikipedia.
    Wikipedia
    suggested: (Wikipedia, SCR_004897)
    In all our regressions, we cluster the standard errors at the county level to account for any potential crosssectional dependence in the error terms, i,j,t . 22 We perform our statistical analysis with STATA 16 and use Sergio Correia’s REGHDFE command to estimate equation (1).
    STATA
    suggested: (Stata, SCR_012763)

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.


    Results from OddPub: Thank you for sharing your data.


    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.