) The primary objective of this research is to inform the development of high-leverage tobacco policies and research. High-leverage policies are those that maximally improve public health or dramatically reduce the economic burden of tobacco use. High-leverage applied research is designed to reduce uncertainty about the critical factors upon which real policy decisions depend. There are many policies and interventions that might reduce tobacco use. Short of performing expensive time-consuming studies, it is difficult to know which policy options are most promising. In the present research, we take a progressive approach toward informing policy. We will develop a rigorous system dynamics computer simulation model which will harness available science to predict the public health and economic consequences of any change in tobacco use in any demographic population and geographical area. Our approach to informing policy is unique in that we abstract away from the myriad of specific policy options to answer more fundamental questions. For example, we will determine which demographic groups are likely to realize the greatest public health gains for a fixed change in tobacco use. This will help decision makers to understand the tradeoffs between policies directed at the young vs. the old, men vs. women, or different racial/ethnic groups. We will also contrast the long term public health and economic consequences of efforts aimed at preventing tobacco use with efforts aimed at the reduction or cessation of tobacco use. To help communities prioritize scarce resources, the model will predict public health gains in all 50 states as well as counties and cities within those states. In addition, we will simulate the long-range outcomes of alternate approaches to safer cigarettes over different time-frames. These include lowering the nicotine content of cigarettes, removing carcinogens, improving access to non-tobacco nicotine delivery devices, and various combinations. Finally, through determining the sensitivity of outcomes to uncertain model parameters, we will identify those parameters that may prove to be good candidates for future high-leverage research. By synthesizing available scientific evidence into a single model, documenting it carefully, and making it available through a user-friendly interface on the Internet, we hope to aid decision makers faced with difficult policy choices.
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