Applying the data science approach to COVID-19 epidemiological modelling to inform PPE demand and supply in Canada

Articles and reports: 11-522-X202100100017
Description: The outbreak of the COVID-19 pandemic required the Government of Canada to provide relevant and timely information to support decision-making around a host of issues, including personal protective equipment (PPE) procurement and deployment. Our team built a compartmental epidemiological model from an existing code base to project PPE demand under a range of epidemiological scenarios. This model was further enhanced using data science techniques, which allowed for the rapid development and dissemination of model results to inform policy decisions.

Key Words: COVID-19; SARS-CoV-2; Epidemiological model; Data science; Personal Protective Equipment (PPE); SEIR

Issue Number: 2021001
Author(s): Hennessy, Deirdre; Barnes, Joel D.; Choi, Jihoon; Baker, Dustin; Tucker, Christina; Hatt, Kayle; Dawson, Gillian; Van Loon, James
Main Product: Statistics Canada International Symposium Series: Proceedings
Format Release date More information
PDF October 22, 2021

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