Improved Estimation of Social Contact Matrices for Modeling the COVID-19 Epidemic in Canada

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Physical distancing is important in order to slow down and control the spread of COVID-19. Without a widely available vaccine, reducing physical contact is crucial, hence the importance of estimating the number of social contacts by population surveys. This project will aim to publish social contact matrices that will be shared with mathematical modellers and Canadian public health authorities to model the evolution of the COVID-19 pandemic.

The social contact matrices will use CONNECT survey data before and during confinement in Canada to establish expected contacts with re-openings currently underway across Canada. This data will then be integrated into this team’s dynamic mathematical model of transmission of COVID-19, developed specifically to guide decision-making in public health in Quebec. Students in this project are led by Alexandre Bureau, Marc Brisson and Mélanie Drolet of the Université Laval. This project, working in collaboration with the Institut national de santé publique du Québec, will enable health authorities to make more data-informed decision in their physical-distancing measures and strategies as well as the gradual lifting of these measures.

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