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Risk of COVID-19 Case Importation and the Effect of Quarantine

Webinar Presented By:  Professor Julien Arino, Department of Mathematics, University of Manitoba

Speaker Bio:  Julien Arino is a professor in the Department of Mathematics and an affiliate of the Data Science Nexus at the University of Manitoba. He is a member of the Canadian Centres for Disease Modelling and the Canadian COVID-19 Mathematical Modelling Task Force. His work is in mathematical ecology and epidemiology, with particular focus on population mobility and its consequences. In the context of COVID-19 response, he has focused on global and local importation risks.

Abstract:  COVID-19 has spread to most country-level jurisdictions. Zooming in, though, it is apparent that not all lower level jurisdictions (e.g., cities) see active disease propagation at all times. This effect is particularly evident in isolated locations such as those in northern Canada or the Maritime provinces. Some locations see active transmission chains for a while, following which no new cases are detected for some time, followed in turn by renewed detections. Two main mechanisms can explain this phenomenon: silent transmission chains and case importations from other locations.

In this work, we focus on importations. We consider a location in which there are few or no local transmission events. A stochastic model is used to describe the spread of COVID-19 within the location and the response of the model to both single and multiple importation events is evaluated. This allows us to quantify the risk of importation as a function of both the frequency of importations and the intensity of local public health effort. We then use the same model to describe individual infection histories, obtaining a quantification of the efficacy of quarantine as a function of its duration and disease characteristics.

Date and Time:  December 9, 2020 | 3:00 p.m. Eastern Time (US and Canada)

Recording of Julien Arino's Webinar

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