I will describe several mathematical models related to covid-19 transmission and their use and application in public health. First I will describe how we have modelled social distancing and its impact using Bayesian estimation and briefly remark on the uses of this modelling structure for short-term forecasting of the impact of higher-transmission variants of concern. Next I will describe modelling vaccination rollout and the advantages of vaccinating essential workers -- defined as those with unavoidable high contact levels at work -- earlier in the vaccination program in Canada.

Caroline Colijn works at the interface of mathematics, evolution, infection and public health. She joined Simon Fraser University Mathematics Department in 2018 as a Canada 150 Research Chair in Mathematics for Infection, Evolution and Public Health. She did her PhD in applied mathematics at the University of Waterloo, where she studied the foundations of quantum mechanics. She changed tack in her postdoctoral years, working on mathematical modelling with Prof. Michael Mackey at McGill and on TB modelling and epidemiology in Megan Murray's group at the Harvard School of Public Health and the Broad Institute at MIT. She moved to the Department of Engineering Mathematics in Bristol, England in 2007 and joined Imperial College London's Department of Mathematics in 2011. She has broad interests in applications of mathematics to questions in evolution and public health, and was a founding member of Imperial's Centre for the Mathematics of Precision Healthcare.

Lab: www.sfu.ca/magpie.html

Relevant publications:

'Vaccine Rollout Strategies: The Case for Vaccinating Essential Workers Early' Vaccine Rollout Strategies: The Case for Vaccinating Essential Workers Early - https://www.medrxiv.org/content/10.1101/2021.02.23.21252309v1

'Quantifying the impact of COVID-19 control measures using a Bayesian model of physical distancing' https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1...