The COVID-19 pandemic has underscored the vital link between epidemiology
and transportation, particularly in the context of activity-travel behavior. While much research has explored the role of mobility in disease spread, there is a notable gap in understanding how individual behavioral choices, especially regarding testing, influence these dynamics. This paper introduces the Mobility-Aware Behavioral Epidemiological Model (MABEM), an innovative framework that integrates activity-based modeling with latent variables to more accurately represent the impact of testing decisions on disease propagation. Using data from the
canton of Vaud, Switzerland, our model simulates the interactions between individual behavior, mobility, and health status, revealing significant underreporting
of infections and highlighting the crucial role of testing choices in shaping observed infection rates. The results suggest that testing behaviors vary significantly
across different demographic groups and regions, influencing both individual activity patterns and overall disease spread. MABEM model proves to be computationally efficient and offers valuable insights for designing targeted public health
interventions. Despite some limitations related to data availability, this research
provides a comprehensive approach to understanding the interplay between mobility, individual behavior, and disease dynamics, offering new possibilities for
more effective disease containment strategies.
@Article{CortKrueBier25,
author = {Cloe {Cortes Balcells} and Rico Krueger and Michel Bierlaire},
title = {Modeling Disease Spread: Integrating Mobility, Awareness, and Behavior},
journal = {Transportation},
year = {2025},
note = {Accepted on Mar 22, 2025}}}
