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CAN-NPI: A Curated Open Dataset of Canadian Non-Pharmaceutical Interventions in Response to the Global COVID-19 Pandemic
Liam G McCoy; Jonathan Smith; Kavya Anchuri; Isha Berry; Joanna Pineda; Vinyas Harish; Andrew T Lam; Seung Eun Yi; Sophie Hu; Canadian Open Data Working Group: Non-Pharmaceutical Interventions; Benjamin Fine.
Afiliação
  • Liam G McCoy; Faculty of Medicine, University of Toronto; Institute of Health Policy, Management and Evaluation, University of Toronto
  • Jonathan Smith; Layer 6 AI
  • Kavya Anchuri; Cumming School of Medicine, University of Calgary
  • Isha Berry; Dalla Lana School of Public Health, University of Toronto
  • Joanna Pineda; Department of Computer Science, University of Toronto; Ontario Institute for Cancer Research
  • Vinyas Harish; Faculty of Medicine, University of Toronto; Institute of Health Policy, Management and Evaluation, University of Toronto
  • Andrew T Lam; Faculty of Medicine, University of Toronto
  • Seung Eun Yi; Layer 6 AI
  • Sophie Hu; Cumming School of Medicine, University of Calgary
  • Canadian Open Data Working Group: Non-Pharmaceutical Interventions;
  • Benjamin Fine; Institute for Better Health, Trillium Health Partners; Department of Medical Imaging, University of Toronto
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20068460
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.
Licença
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Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
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