Speaker: Dionne Aleman, Associate Professor, Industrial Engineering
Thursday, April 1, 2021
Location: Virtual – join us on Zoom!
A Fast and Granular Agent-Based Simulation Model of COVID-19
Abstract: Most COVID-19 projections are based on compartmental models, which require only high-level information about a disease and population to make high-level predictions. For nuanced assessment of policy interventions to slow disease spread, agent-based simulation (ABS) models that treat individuals uniquely are more appropriate, but can be computationally unwieldy and even intractable. The Medical Operations Research Lab’s Pandemic Outbreak Planner (morPOP) is a computationally tractable, memory efficient ABS that considers the unique demographic, comorbidity, and behavior characteristics of each individual. It has been used to model H1N1 and pandemic influenza in the Greater Toronto Area (6 million agents) and is currently used to model COVID-19 in Newfoundland & Labrador (520,000 agents). Specific scenarios examined with morPOP include school mitigation measures and the effectiveness of NL’s travel ban, allowing public health officials to make evidence-based decisions about appropriate measures to enact.
Recording at: U of T MIE Youtube channel