Agent-Based Modeling in Public Health: Current Applications and Future Directions
By Melissa Tracy, M. Cerdá, Katherine M. Keyes. Annual Review of Public Health, 2018
321 citations recorded by the source corpus.
Agent-based modeling is a computational approach in which agents with a specified set of characteristics interact with each other and with their environment according to predefined rules. We review key areas in public health where agent-based modeling has been adopted, including both communicable and noncommunicable disease, health behaviors, and social epidemiology. We also describe the main strengths and limitations of this approach for questions with public health relevance. Finally, we describe both methodologic and substantive future directions that we believe will enhance the value of agent-based modeling for public health. In particular, advances in model validation, comparisons with other causal modeling procedures, and the expansion of the models to consider comorbidity and joint influences more systematically will improve the utility of this approach to inform public health research, practice, and policy.
Subfields: Health, Management Science and Operations Research, Modeling and Simulation
View Paper: https://www.semanticscholar.org/paper/ebc3c689a69f536d0b089d00cb19c8e8cce0f648
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In Management Science and Operations Research
- Fotios Petropoulos
- Rob J Hyndman
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In Modeling and Simulation
Citations in the corpus
- Forecasting: theory and practice (2020, background): “Despite these limitations and challenges, agent-based modelling has been used extensively to model infectious disease transmission and forecasting (Tracy et al., 2018; Venkatramanan et al., 2018).”
- Nanomedicine-Driven Modulation of the Gut–Brain Axis: Innovative Approaches to Managing Chronic Inflammation in Alzheimer’s and Parkinson’s Disease (2025, unknown): “However, increased complexity requires careful consideration of essential system components [282].”