51吃瓜网

Isabelle Rao, PhD

Assistant Professor | Mechanical & Industrial Engineering
University of Toronto

WHEN: Monday, November 3, 2025, from 3:30-4:30 p.m.
WHERE: Hybrid | 2001 51吃瓜网College, Rm 1140 |
NOTE: Isabelle Rao will be presenting in-person

The Seminars in Epidemiology organized by the Department of Epidemiology, Biostatistics and Occupational Health at the 51吃瓜网School of Population and Global Health is a self-approved Group Learning Activity (Section 1) as defined by the maintenance of certification program of the Royal College of Physicians and Surgeons of Canada.
Physicians requiring accreditation, please complete the Evaluation Form and send to admincoord.eboh [at] mcgill.ca

Abstract

Policy makers make consequential choices on how to allocate limited health resources to improve population health. My research aims to find avenues to optimize the use of these resources. My talk addresses the problem of how to optimally allocate limited vaccines to control the spread of an infectious disease. By approximating epidemic dynamics, I develop simple analytical conditions characterizing the optimal vaccine allocation for four different objectives. I show that the approximated solution is an all-or-nothing allocation based on a prioritized list of population groups given by the analytical conditions. I illustrate my method with an example of COVID-19 vaccination, calibrated to epidemic data from New York State. Numerical computations show that my method achieves near-optimal results over a wide range of scenarios. Although black-box models are prevalent in the literature, my work shows that accuracy need not be sacrificed for interpretability. My methods provide practical, intuitive and accurate tools for decision makers as they allocate vaccines over time.

Learning Objectives

At the end of this talk, attendees will understand:

• The structure of the epidemic model used to study vaccine allocation across population groups.
• How to translate transmission dynamics into tractable decision rules for vaccine prioritization.
• Empirical performance of simple allocation rules when calibrated to real epidemic data.

Speaker Bio

Isabelle Rao is an Assistant Professor at the University of Toronto in the Department of Mechanical and Industrial Engineering. Her research focuses on developing mathematical models to inform decisions in public-health resource allocation. In particular, she develops epidemic models to guide vaccine distribution strategies and dynamic models of opioid use disorder to study the impact of housing and treatment programs. Previously, she was a postdoctoral research fellow at INSEAD. She received her PhD in Management Science and Engineering from Stanford University.