Public policies (laws, regulations, penalties) concerning alcohol and car safety have contributed to important declines in traffic fatalities over the past thirty years. But there is still enormous variation in the number and type of effective public policies different states have adopted. The study will use systems science tools (network analysis and dynamical systems modeling) to characterize the interaction of multiple policies (e.g. those associated with alcohol availability and use, risky driving, and car safety) across all 50 states over time. The goals of the project ar to formulate and refine a mathematical model using network theory to explain the dynamic process of state alcohol and safer driving policy adoption and diffusion over time;and apply the final model to estimate the impact of state health laws on traffic fatalities. The project's end result will be a tested and validated mathematical model that will inform understanding of the dynamic and interconnected nature of alcohol and related laws, their adoption, and their effects on health outcomes.
The study will demonstrate the use of network analysis to explain the adoption, diffusion, and impact of effective policy-based approaches to reducing deaths and injuries from alcohol and motor vehicles within US states. Project aims are consistent with Healthy People 2020 objectives of reducing traffic fatalities by 10 percent and NIAAA's priorities for assessing the alcohol policy environment.