Application Background: Designing Policy Options for Obesity Prevention

• Goal /Aspiration for Project
• Ability to analyze and compare effects of possible policy interventions to reduce the public health impact of obesity and overweight through the identification of policy cocktails that address multiple aspects of the obesity problem, resulting in amplification of desirable results with strong uncertainty reduction.
• Approach/Methods/Models
• The IBM uses a social network to simulate the spread of opinions relating to nutrition and physical activity (N&PA) behaviors such as dieting and exercise, and the effects of these opinions on individual actions.
• The network structure uses a mixture of scale-free and uniformly random connections to represent a social network of relationships and interactions within a local community.
• The N&PA related health behaviors of individuals change dynamically relative to endogenous influences within their social network and exogenous influences from industry-based advertising and public health-related counter-marketing and educational campaigns.
• The outputs of the IBM, seen as changes in obesogenic behaviors, can be used as inputs to a SD model to calculate the resulting changes in mortality and morbidity over the ensuing decades.
• Status, Accomplishments and Next Steps
• Collaboration initiated in FY11
• Continued expansion of model incorporating additional opinions, behaviors, and policy-based interventions
• Correlation of analysis with empirical datasets
• Application of model to analyze dynamics and design policies in real world communities
• CASoS Goals: General Capabilities
• Utilization of the interface between agent-based models and system dynamics models at varying scales
• Understanding of the spread of health behaviors
• Identification of network effects using virtual populations and multi-methods
• CASoS Goals: Other Potential Applications
• Multi-scale modeling applications
• Opinion formation applications
• Acknowledgements
• We gratefully acknowledge the feedback of John Sterman and PJ Lamberson on the development of this work, as well as the use of Jack Homer’s PRISM model
• Previous development of CASoS health behavior and opinion dynamics modeling for the Veterans Health Administration and the US Health and Human Services agency was also key to the success of this application