Miller investigates the possible impacts of control measures on disease spread

Professor Eric J. Miller presented “Using an Agent/Activity-Based Microsimulation Model to Test COVID-19 Control Strategies: Model Design & Preliminary Results” for the UT-ITE seminar series on November 13, 2020. He spoke about modelling disease spread through a study of scenarios comparing different control strategies for slowing down COVID-19 infection.

There is a careful balance between quarantining, which causes human and economic cost, and lifting restrictions, which threatens health care systems and people through resurging infections. Miller notes that all levels of government need to find the best policies for easing restrictions while limiting disease spread.

Typical models for disease spread include “SIR” (Susceptible, Infected, Removed) models which do not show finer details like no spatial, socio-demographics/economics, or household and other social network components. To account for these shortcomings, the Travel/Activity Scheduler for Household Agents (TASHA) model was developed at the University of Toronto. This model builds each person’s daily schedule using probabilities for activities, handles complex tours, and deals with household-level interactions. 

For real-world use, TASHA is embedded into an overall model system such as the GTAModel V4 which is in use for the Greater Toronto Area. 

Colleagues at the University of New South Wales have applied TASHA to the Sydney Greater Metropolitan Area for testing COVID-19 control strategies. Through an integrated model, the SydneyGMA Model interacts with the disease spread model, analyzing each agent and updating their disease state. System parameters that affect disease states included travel-behaviour specific, disease-specific, and policy-specific parameters. Control strategy scenarios included social distancing compliance, speed of implementation of lockdown, demand load and quarantining family members, and face masks. The model showed that there was little benefit for social distancing compliance levels of less than 50% and a one-week delay in enforcing lockdown could increase cases by 700%.

For COVID-19 and modelling in the GTHA, the City of Toronto asked for a modified GTAModel to  compare COVID-19 scenarios with base case scenarios such as changing labour force participation rates and adjusting school trip-making rates. There are plans to develop, test scenarios, calibrate, and refine the proposed GTAModel C19, which is in Phase 1 of a two-phase work plan.

professor standing in front of colourful bookshelves
Professor Eric J. Miller

Eric J. Miller is Director of the University of Toronto Transportation Research Institute, Research Director of the Data Management and Travel Modelling Groups, and Professor of Civil Engineering at the University of Toronto.

He is Past Chair of the U.S. Transportation Research Board (TRB) Committee on Travel Behavior and Values, Member Emeritus of the TRB Transportation Demand Forecasting Committee and Past Chair of the International Association for Travel Behaviour Research (IATBR). He served on the US National Academy of Sciences Committee for Determination of the State of the Practice in Metropolitan Area Travel Forecasting. He has chaired or been a member of numerous travel demand modelling peer review panels throughout North America.

He is the recipient of the 2009 Wilbur S. Smith Distinguished Educator Award from the Institute of Transportation Engineers, the inaugural winner of the University of British Columbia Margolese National Design for Living Award (2012) and recipient of the 2018 IATBR Lifetime Achievement Award.

Miller is the developer of GTAModel, an advanced regional travel demand modeling system used by municipalities in the Greater Toronto Area (GTA) to forecast travel demand that is based on TASHA, a state-of-the-art agent-based microsimulation model of activity and travel, and ILUTE, an integrated land use-transportation model system for the GTA.

Presented by University of Toronto ITE Student Chapter, UT-ITE.