CAN-NPI: A Curated Open Dataset of Canadian Non-Pharmaceutical Interventions in Response to the Global COVID-19 Pandemic

  1. Liam G. McCoy
  2. Jonathan Smith
  3. Kavya Anchuri
  4. Isha Berry
  5. Joanna Pineda
  6. Vinyas Harish
  7. Andrew T. Lam
  8. Seung Eun Yi
  9. Sophie Hu
  10. COVID-19 Canada Open Data Working Group: Non-Pharmaceutical Interventions
  11. Benjamin Fine

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Abstract

Non-pharmaceutical interventions (NPIs) have been the primary tool used by governments and organizations to mitigate the spread of the ongoing pandemic of COVID-19. Natural experiments are currently being conducted on the impact of these interventions, but most of these occur at the subnational level - data not available in early global datasets. We describe the rapid development of the first comprehensive, labelled dataset of 1640 NPIs implemented at federal, provincial/territorial and municipal levels in Canada to guide COVID-19 research. For each intervention, we provide: a) information on timing to aid in longitudinal evaluation, b) location to allow for robust spatial analyses, and c) classification based on intervention type and target population, including classification aligned with a previously developed measure of government response stringency. This initial dataset release (v1.0) spans January 1st, and March 31st, 2020; bi-weekly data updates to continue for the duration of the pandemic. This novel dataset enables robust, inter-jurisdictional comparisons of pandemic response, can serve as a model for other jurisdictions and can be linked with other information about case counts, transmission dynamics, health care utilization, mobility data and economic indicators to derive important insights regarding NPI impact.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.17.20068460: (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: We detected the following sentences addressing limitations in the study:
    Limitations: Due to our reliance on public information and releases in creating this dataset, it is possible that interventions that were not publicly announced may have been omitted from the dataset. For example, Nunavut is offering up to $5000 in support for businesses in the territory, but they give no indication of the number of eligible businesses15, and thus we could not compute and report a total fiscal value. Similarly, testing policy changes that were not communicated directly to the public through online announcements, such as substantial shifts in practice occurring within public health units and hospitals (e.g. whether or not a testing referral is accepted), may not have been captured in this dataset. There is inherent variability in how different jurisdictions choose to report and describe their NPIs, as well as the range of information that they choose to include or not include. This may have introduced a degree of variability in our labelling. We have sought to minimize inconsistencies across jurisdictions and reviewers through the aforementioned standardized onboarding process, step-wise data-entry, and a secondary, focused review by a smaller group of reviewers prior to data release. Moreover, as residual variation is likely due to subjective differences rather than error, the open nature of our data allows for end users to suggest future improvements to our dataset or download it to make modifications to suit their specific research needs.

    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 10.1101/2020.04.17.20068460 on medRxiv