Keywords: Stochastic System Dynamics Models, Multi-feature Models, Agent-based Models, Social Dynamic Networks
Tobacco is among the principal preventable causes of morbidity and mortality worldwide. Since 2009 the US-FDA is authorized to regulate the manufacturing and marketing of tobacco products in the US. A critical component of tobacco regulation is to examine the impact of tobacco products on the population as a whole, including, users and non-users. To assess the long-term population impact of regulatory actions, require novel modeling and simulation approaches. This presentation provides an overview of modeling and simulation frameworks such as dynamic social networks, agent-based models, stochastic systems dynamic models, and hybrid multi-feature models with applications in tobacco regulatory science.