Simulation modeling and tobacco control: creating more robust public health policies.
Although previous empirical studies have shown that tobacco control policies are effective at reducing smoking rates, such studies have proven of limited effectiveness in distinguishing how the effect of policies depend on the other policies in place, the length of adjustment period, the way the policy is implemented, and the demographic groups considered. An alternative and complementary approach to purely statistical equations is simulation models. We describe the SimSmoke simulation model and how we used it to assess tobacco control policy in a specific case study. Simulation models are not only useful for policy prediction and planning but also may help to broaden our understanding of the role of different public health policies within a complex, dynamic social system.
Levy
David T
DT
11710 Beltsville Drive, Suite 300, Calverton, MD 20705. levy @pire.org.
Bauer
Joseph E
JE
Lee
Hye-Ryeon
HR
D000293:Adolescent; D003198:Computer Simulation; D006291:Health Policy / Q000331:legislation & jurisprudence*; D006801:Humans; D015233:Models, Statistical; D012907:Smoking / Q000453:epidemiology* / Q000331:legislation & jurisprudence*; D016540:Smoking Cessation; D000074606:Smoking Prevention