A Control-Theoretic Assessment of Interventions During Drinking Events.

Area of Science:

• Control theory
• Network science
• Public health

Background:

• High-risk alcohol consumption at drinking events poses significant public health challenges.
• Effective in-situ interventions are needed to mitigate negative health outcomes associated with excessive alcohol intake.

Purpose of the Study:

• To develop a control-theoretic framework for guiding interventions aimed at reducing alcohol consumption.
• To identify optimal intervention strategies within drinking event networks.

Main Methods:

• A dynamical directed network model of drinking events incorporating external interventions was developed.
• Lyapunov stability analysis and graph-theoretic methods were used to assess system controllability.
• The degree of controllability, derived from the controllability Gramian, was employed to evaluate intervention node viability.

Main Results:

• Mathematical analysis provided bounds on blood alcohol content (BAC) trajectories and structural controllability guarantees.
• Numerical examples simulating bars and parties, informed by field data, demonstrated intervention effectiveness.
• Intervening in the environment of 'wet' bars and targeting influential individuals in private parties were identified as efficient strategies.

Conclusions:

• Control-theoretic tools offer valuable guidelines for designing effective interventions against high-risk alcohol consumption.
• The study highlights the importance of network structure and individual influence in intervention planning.
• Targeted interventions can significantly reduce peak BAC levels at drinking events.