Making sense of publicly available data on COVID-19 in Ireland

  1. Gerald Mills
  2. Walter Cullen
  3. Niamh Moore
  4. Ronan Foley

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Abstract

This paper reports on the management of the COVID19 pandemic in Ireland over the period March to May 2020. During this period the Irish government implemented a series of policies designed to delay the spread of the pandemic culminating in a stay-at-home order that greatly restricted mobility for the majority of the population. In this paper we evaluate the policies enacted using evidence obtained from a number of novel sources, including census and real-time traffic data. The evidence suggests that the policies have impeded the spread of the virus, which has mostly been confined to Dublin and its commuter belt. At the same time, the virus has become concentrated in a number of clusters associated with nursing homes and workplaces that remained open during the delay phase. This evidence is used to hypothesise on the likely impact of the pandemic on high density and poor neighbourhoods in Dublin.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.13.20101089: (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.

  2. Version published to 10.1101/2020.05.13.20101089v1 on medRxiv