Advertisement
AJPH
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH
QUICK SEARCH:   [advanced]


     

AJPH First Look, published online ahead of print Jan 31, 2006
This Article
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
AJPH.2005.063974v1
96/3/494    most recent
Right arrow Submit a response
Right arrow purchase articles
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Right arrow Get other permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Levy, D. T.
Right arrow Articles by Lee, H.-r.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Levy, D. T.
Right arrow Articles by Lee, H.-r.
©
American Journal of Public Health, 10.2105/AJPH.2005.063974

Analytic Essay Forum

Simulation Modeling and Tobacco Control: Creating More Robust Public Health Policies

David T. Levy 1*, Joseph E. Bauer 2, Hye-ryeon Lee 3

1 Pacific Institute and University of Baltimore
2 Roswell Park Cancer Institute
3 University of Hawaii at Manoa

* To whom correspondence should be addressed. E-mail: levy{at}pire.org.


  Abstract

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.

Key Words: Epidemiology, Health Administration, Health Policy, Prevention, Public Health Practice




This article has been cited by other articles:


Home page
 Health Promot PractHome page
M. Eisenberg
Integrating a School-Based Health Intervention in Times of High-Stakes Testing: Lessons Learned From Full Court Press
Health Promot Pract, April 1, 2009; 10(2): 284 - 292.
[Abstract] [PDF]

Home page
 Cancer Epidemiol. Biomarkers Prev.Home page
A. M. Hartman, M. J. Thun, R. Ballard-Barbash, and for the Organizing Committee
Linking Tobacco Control Policies and Practices to Early Cancer Endpoints: Surveillance as an Agent for Change
Cancer Epidemiol. Biomarkers Prev., September 1, 2008; 17(9): 2215 - 2219.
[Abstract] [Full Text] [PDF]

Home page
 Tobacco ControlHome page
D T Levy, S Benjakul, H Ross, and B Ritthiphakdee
The role of tobacco control policies in reducing smoking and deaths in a middle income nation: results from the Thailand SimSmoke simulation model
Tob. Control, February 1, 2008; 17(1): 53 - 59.
[Abstract] [Full Text] [PDF]


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH
Copyright © 2006 by the American Public Health Association