A Framework to Incorporate Human Behavior in Agent-Based Models for Infectious Disease: Insights From Health Behavior Theories
提出一个整合经典行为理论与心理构念的建模框架，指导传染病模拟中如何科学地表示人类行为，帮助模型设计者利用实证数据校准和验证模型。
Agent-based models (ABMs) are critical for projecting and responding to infectious disease outbreaks, yet the effectiveness of health interventions heavily relies on individual adherence, underscoring the importance of accurately representing human behavior. While some ABMs have incorporated behaviors, clear guidelines for leveraging the extensive literature on behavioral theories have been lacking. This study addresses this challenge by proposing a modeling framework that integrates classical behavioral theories and their psychological constructs, drawing upon well-established definitions and categorizations from the social sciences to guide operationalization. We present novel and existing modeling approaches to represent these constructs and their interactions with the environment and behavior. Furthermore, we discuss methods for determining an agent’s likelihood of adopting a behavior and how empirical data can be used for calibration and validation. To illustrate the application of the framework to disease-specific behaviors, we provide a modeling example. Ultimately, this proposed framework offers a roadmap for computational modelers to incorporate scientifically grounded behaviors in the design and evaluation of simulation models and interventions.