Tobacco products can lead to chronic health effects that can take decades to manifest (e.g., lung cancer can take 20+ years), which would require long-term studies to assess. Population models and simulations provide a desirable alternative for making estimates and predictions of likely impact on morbidity/mortality at the population level in the absence of empirical data. Mathematical, computational, and simulation models can also help guide regulatory activities such as new product authorizations and policy development. Such models take into consideration both users and nonusers of tobacco products and include but are not limited to cohort models, agent-based models, deterministic and stochastic systemic dynamic models, and static and dynamic social network models. Examples in this section illustrate how CDISC analysis standards represent parameters used as inputs to such modeling.
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