COVID CRISIS LAB Seminar Series 2022 — Fall edition
Chris Bauch, "Using behavioural epidemiology models to inform COVID-19 vaccine prioritisation"
During the COVID-19 pandemic, authorities must decide which groups to prioritise for vaccination in an evolving landscape where infection dynamics and population behaviour influence one another. Moreover, if vaccines prevent not only disease but also transmission, authorities must factor vaccine indirect protection (vaccine-generated herd immunity) into their considerations, which may suggest a strategy of targeting groups that cause the most transmission. This talk will use a mathematical model to address the question: which age group should be prioritized for COVID-19 vaccination to prevent the most deaths? We developed an age-structured human-environment mathematical model for Ontario, Canada, where a coupled behaviour-disease model describes how population adherence to non-pharmaceutical interventions (NPIs) responds to case incidence. We compared strategies of vaccinating 60+ year-olds first; <20 year-olds first; uniformly by age; and a novel contact-based strategy. The last three strategies interrupt transmission while the first targets a vulnerable group. The model shows realistic dynamics whereby case notifications, NPI adherence, and lockdown undergo successive waves that interact with timing of the vaccine program to determine the relative effectiveness of the four strategies. Although vaccinating older age groups is more effective in most parameter regimes, we also identify a parameter regime where transmission-interrupting strategies are more effective in reducing deaths. The effectiveness of vaccination strategies may also depend on the time course of the pandemic in a population. We conclude that behavioural epidemiology models can be useful for making decisions about vaccine prioritisation during the COVID-19 pandemic. This is joint work with Madhur Anand and Peter Jentsch.
Professor Chris Bauch is a professor in the Department of Applied Mathematics at the University of Waterloo. His research program applies mathematics to real-world problems in infectious diseases, ecology, social science, and sustainability. He has been studying mathematical models of infectious disease spread for 23 years, including for SARS in 2003 and pandemic influenza in 2009. He has also been developing mathematical models for the COVID-19 pandemic. Professor Bauch uses models to further our scientific understanding of infectious disease dynamics, as well as to make projections of future disease spread, in order to inform public health policy. For infectious diseases, modelling can be used to assess control strategies like mask-wearing or vaccination. His particular focus is on how infectious disease spread responds to interventions like physical distancing and vaccines. Professor Bauch’s research partners have included the World Health Organization, the United States Food and Drug Administration, and the Bill and Melinda Gates Foundation.
For further information on the talk, please contact firstname.lastname@example.org