Testing the effects of the timing of application of preventative procedures against COVID-19: An insight for future measures such as local emergency brakes

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Abstract

As many countries plan to lift lockdown measures aimed at suppression of COVID-19, data from early regional epidemics in Italy were analysed to ascertain the effectiveness of the timing of preventative measures. The cumulative caseload data were extracted from regional epidemics in Italy. Epidemic features in regions where lockdown was applied early were compared to those where lockdown was applied later for statistical differences. There were statistically significant differences in the timing of the peak, the cumulative incidence at peak and the case/km 2 at peak between regions where the lockdown had been applied early and those where it was applied late. The peak occurred 7 days earlier with four times less cases/km 2 in regions where the lockdown was applied within 10 days of the start of the epidemic. Cumulative caseloads, cases/km 2 and/or the number of days into an epidemic can be used to plan future localised suppression measures as part of a national post-lockdown policy. There were 350 (95% confidence interval (CI) 203) cumulative cases and 2.4 (CI 1.1) cases/km 2 on day 8 of the regional epidemics.

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  1. SciScore for 10.1101/2020.06.02.20120352: (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

    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: 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 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.