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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. 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 . Various types of population models may be used for these purposes, and include cohort models, agent-based models, deterministic and stochastic systemic dynamic models, and static and dynamic social network models.
(stopped here on 7/7 - discuss inputs at a high-level next?)

In this section, these models are discussed with regard to inputs to, and outputs from the models, and how these models contribute to studies of tobacco products, how they are represented in CDISC standards for submission to a regulatory authority.

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