Agent-Based Modeling

Agent-based models are computer simulations used to study the interactions between people, things, places, and time. They are stochastic models built from the bottom up meaning individual agents (often people in epidemiology) are assigned certain attributes. The agents are programmed to behave and interact with other agents and the environment in certain ways. These interactions produce emergent effects that may differ from effects of individual agents. Agent-based modeling differs from traditional, regression-based methods in that, like systems dynamics modeling, it allows for the exploration of complex systems that display non-independence of individuals and feedback loops in causal mechanisms. It is not limited to observed data and can be used to model the counterfactual or experiments that may be impossible or unethical to conduct in the real world. However, agent-based modeling is not without its limitations. The data parameters (such as the reproductive rate for infectious diseases) are often difficult to find in the literature. In addition, the validity of the model can be difficult to assess, particularly when modeling unobserved associations. Overall, agent-based models provide an additional tool for assessing the impacts of exposures on outcomes. It is particularly useful when interrelatedness, reciprocity, and feedback loops are known or suspected to exist or when real world experiments are not possible.




Systems science methods in public health: dynamics, networks, and agents

Social network analysis and agent-based modeling in social epidemiology

Causal thinking and complex system approaches in epidemiology


Agent-based simulation platforms: review and development recommendations

Modeling and analysis of global epidemiology of avian influenza


Modeling targeted layered containment of an influenza pandemic in the United States

Conceptual approaches to the study of health disparities

Understanding long-term diffusion dynamics in the prevalence of adolescent sexual initiation: A first investigation using agent-based modeling

The role of subway travel in an influenza epidemic: a New York City simulation

A spatial agent-based model for the simulation of adults’ daily walking within a city

Using simple agent-based modeling to inform and enhance neighborhood walkability