Abstract

This paper employs control-theoretic tools to provide guidelines for in-situ interventions aimed at reducing high-risk alcohol consumption at drinking events. A dynamical directed network model of a drinking event with external intervention, suitable for mathematical analysis and parameter estimation using field data is proposed, with insights from pharmacokinetics and psychology. Later, a characterization of a bound on blood alcohol content (BAC) trajectories is obtained via Lyapunov stability analysis, and structural controllability guarantees are obtained via a graph-theoretic method. We use the degree of controllability, given to be the trace of the system's controllability Gramian, as a metric to compare the viability of network nodes for intervention based on theoretic and heuristic centrality measures. Results of numerical examples of bars and parties, informed by field data, and the stability and controllability results, suggest that intervening in the environment in wet bars, while targeting influential individuals with high alcohol consumption motivations in private parties efficiently yield lower peak BAC levels in individuals at the drinking events.

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