HC-Population Health
Decision-making model to optimize the impact of community-based health programs
Goal:
An agent-based simulation model is combined with an optimization model to select the optimal mix of community-based health programs based on the profiles of the population.
Funded by: National Institute of Health (NIH)
Principal Investigators: Dr. Eduardo Pérez, Dr. Jose Pagán (New York University), and Dr. Yan Li (Icahn School of Medicine)
Collaborators:
Students:
Agent based simulation model in AnyLogic
Simulation optimization framework
- The red dotted line is used to highlight the data and actors (i.e., community, public health decision makers, and prevention programs) involved in the implementation of the decision-making model.
- The outputs from the agent-based model were used as input parameters to the decision-making model that seeks to optimize funding decisions in terms of which community-based health program
Simulation optimization framework
Research publications
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Pérez, E., Y. Li, and J.A. Pagán (2021) “A Decision-Making Model to Optimize the Impact of Community-Based Programs” Preventive Medicine, Vol. 149.