Incorporating Face Mask Usage in Agent-Based Models Using Personal Beliefs and Perceptions: An Application of the Health Belief Model

The modelling of human behavior is a critical component of any simulation tool that aims to represent the spread of an infectious disease throughout a population. However, few modeling approaches attempt to incorporate protective behaviors using models grounded in theories from the behavioral sciences. Here, we demonstrate how to incorporate human behavior accounting for personal beliefs and perceptions by using a commonly known behavioral framework. We implemented the proposed model within an agent-based simulation to drive the agent's decision related to wearing a face mask. We used survey data to characterize a synthetic population, and investigate the effect of policies that aim to modify beliefs with the goal of promoting face mask usage. Our results highlight the importance of incorporating the individual drivers of behavior to better represent adoption of protective actions against health threats, enhancing the ability of simulation tools to quantify the impact of policy interventions.