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PACIFIC INSTITUTE FOR RESEARCH AND EVALUATION


    

Indonesia


Analysis of smoking prevalence reduction in nineteen countries using the estimated policy effect size of the SimSmoke model.


Principal Investigator:

David Levy

Sponsor:

World Lung Foundation
07/19/10 - 10/25/11
This consulting project would use the estimated policy effect sizes from SimSmoke model to a) predict the effect of policies implemented during 2008 that have been implemented by countries meeting one or more of the MPOWER goals, and b) compare those results to the effects as shown by SimSmoke models for two selected countries. These results in b) will be used to show the limitations in using the simpler estimates in a) and to suggest ways of evaluating the effect of MPOWER policies implemented in the future. Specifically, The Consultant agrees to perform the following activities: 1) Collection of data. The following data would be required: a. Current and past policies. b. Population data to determine the number of smokers. c. Smoking rates distinguishing males and females. d. Death rates 2) Develop estimates for each country: a. Calculate the change in smoking rate as a result of reaching the MPOWER goal for each country in terms of 1) 3 years after the policy is implemented (i.e., the short term effect) and 2) 20 years after the policy is implemented (i.e., the long term effect). b. Calculate the reduction in smokers in the short-term and long term c. Calculate the number of lives saved for each country based on the formula that half of smokers will die from smoking related causes based on long-term and short-term estimates of reduction in smokers. d. For all nations as total calculate: i) the reduction in smokers and ii) the number of lives saved for all nations reaching the MPOWER goals. 3) Use models for two nations to validate: The previously developed Turkey and Egypt models will be use to show how the effects on smoking prevalence, number of smokers and deaths attributable to smoking evolve over time using a more sophisticated model. 4) Write report that includes: a. Description of methodology b. Results by nation and for the two SimSmoke nations c. Limitations of the analysis and suggested future analyses for the  purposes of evaluation 5) Review and re-write of report based on suggestions of Bloomberg staff. 6) Produce a paper for a peer-reviewed journal, to be submitted upon completion of project. Journal-requested rewrites are included in estimate.

 

Modeling the Effects of MPOWER Policies Using the SimSmoke Model


Principal Investigator:

David Levy

Sponsor:

Bloomberg Family Foundation
04/02/08 - 09/30/08
The SimSmoke simulation model first projects the smoking prevalence and smoking-attributable deaths over time (usually a 20 year period time period) from the most recent year onward. First, the model estimates these outcomes in the absence of any policy change (status quo), and then estimates the effect of tobacco control policies on those outcomes. The model has been described in a series of over 25 articles, and has been shown to predict well at the national and state level. The model has been developed for 6 different states and 10 different nations. Medium to low income nations include: Albania, Argentina, Korea, Malaysia, Thailand, and Viet Nam. The nation models have been set up to estimate the effect of a set of policies, individually and in combination, that are consistent with the FCTC. The model for each model requires national data on population, mortality rates, fertility rates, smoking rates (broken down by never smoker, smoker and ex-smoker categories), and information on the policies currently in effect. Except for policy information, the data for the initial year is generally broken down by gender and then by 5-10 year/age groups. Statement of Work Develop models for the following low/middle income nations: China, India, Indonesia, Russia, Bangladesh, Brazil, Mexico, Turkey, Pakistan, Egypt, Ukraine, Philippines, Thailand, Vietnam, Poland; and the following high income nations: US, Japan, and Germany. For the purposes of this project, we would begin the model in the year 2008, but would use smoking prevalence data for the most recent year for which there is a large scale survey of smoking prevalence. Prevalence data will be collected using existing published surveys, data already held by Dr. Levy, or from the World Health Organization's InfoBase.* Each nation model would predict the number of smokers, the smoking prevalence, and smoking-attributable deaths. We would predict status quo levels and levels when MPOWER policies are implemented, as specified by Bloomberg Philanthropies (BP) staff.