Yiqing Xia, Jorge Luis Flores Anato, Caroline Colijn, Naveed Janjua, Mike Irvine, Tyler Williamson, Marie B Varughese, Michael Li, Nathaniel Osgood, David J D Earn, Beate Sander, Lauren E Cipriano, Kumar Murty, Fanyu Xiu, Arnaud Godin, David Buckeridge, Amy Hurford, Sharmistha Mishra, Mathieu Maheu-Giroux
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引用次数: 0
Abstract
Setting: Mathematical modelling played an important role in the public health response to COVID-19 in Canada. Variability in epidemic trajectories, modelling approaches, and data infrastructure across provinces provides a unique opportunity to understand the factors that shaped modelling strategies.
Intervention: Provinces implemented stringent pandemic interventions to mitigate SARS-CoV-2 transmission, considering evidence from epidemic models. This study aimed to summarize provincial COVID-19 modelling efforts. We identified modelling teams working with provincial decision-makers, through referrals and membership in Canadian modelling networks. Information on models, data sources, and knowledge translation were abstracted using standardized instruments.
Outcomes: We obtained information from six provinces. For provinces with sustained community transmission, initial modelling efforts focused on projecting epidemic trajectories and healthcare demands, and evaluating impacts of proposed interventions. In provinces with low community transmission, models emphasized quantifying importation risks. Most of the models were compartmental and deterministic, with projection horizons of a few weeks. Models were updated regularly or replaced by new ones, adapting to changing local epidemic dynamics, pathogen characteristics, vaccines, and requests from public health. Surveillance datasets for cases, hospitalizations and deaths, and serological studies were the main data sources for model calibration. Access to data for modelling and the structure for knowledge translation differed markedly between provinces.
Implication: Provincial modelling efforts during the COVID-19 pandemic were tailored to local contexts and modulated by available resources. Strengthening Canadian modelling capacity, developing and sustaining collaborations between modellers and governments, and ensuring earlier access to linked and timely surveillance data could help improve pandemic preparedness.
期刊介绍:
The Canadian Journal of Public Health is dedicated to fostering excellence in public health research, scholarship, policy and practice. The aim of the Journal is to advance public health research and practice in Canada and around the world, thus contributing to the improvement of the health of populations and the reduction of health inequalities.
CJPH publishes original research and scholarly articles submitted in either English or French that are relevant to population and public health.
CJPH is an independent, peer-reviewed journal owned by the Canadian Public Health Association and published by Springer.
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La Revue canadienne de santé publique se consacre à promouvoir l’excellence dans la recherche, les travaux d’érudition, les politiques et les pratiques de santé publique. Son but est de faire progresser la recherche et les pratiques de santé publique au Canada et dans le monde, contribuant ainsi à l’amélioration de la santé des populations et à la réduction des inégalités de santé.
La RCSP publie des articles savants et des travaux inédits, soumis en anglais ou en français, qui sont d’intérêt pour la santé publique et des populations.
La RCSP est une revue indépendante avec comité de lecture, propriété de l’Association canadienne de santé publique et publiée par Springer.