Counterfactual COVID-19: Modeling Alternative Mitigation and Vaccination Policies for Canada

MarwaTuffaha

York University

"Counterfactual COVID-19: Modeling Alternative Mitigation and Vaccination Policies for Canada"

COVID-19, a global pandemic with severe health and economic repercussions, has prompted various approaches to mitigate its impact. We adapt an age-structured SEIVS model—incorporating waning immunity and partial protection—to explore counterfactual scenarios of non-pharmaceutical interventions (e.g., school/workplace closures, distancing) and selected vaccine policy changes in Canada. By altering contact patterns and compliance levels, we assess potential outcomes under stricter, earlier, or more relaxed mitigation measures, with a lesser emphasis on shifting vaccination rollouts. Findings indicate that timely, robust mitigation can substantially reduce severe disease and delay epidemic peaks, whereas delayed or minimal interventions lead to higher case burden. Integrating vaccine strategies into these scenarios further highlights the interplay between pharmaceutical and non-pharmaceutical measures, showcasing how modeling can inform dynamic policy-making for ongoing and future public health crises.
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