Dennis M Gorman1, Jadranka Mezic, Igor Mezic, Paul J Gruenewald. 1. Department of Epidemiology and Biostatistics, School of Rural Public Health, Texas A&M Health Science Center, College Station, TX 77843-1266, USA. gorman@srph.tamhsc.edu
Abstract
OBJECTIVES: We developed a preliminary agent-based simulation model designed to examine agent-environment interactions that support the development and maintenance of drinking behavior at the population level. METHODS: The model was defined on a 1-dimensional lattice along which agents might move left or right in single steps at each iteration. Agents could exchange information about their drinking with each other. In the second generation of the model, a "bar" was added to the lattice to attract drinkers. RESULTS: The model showed that changes in drinking status propagated through the agent population as a function of probabilities of conversion, rates of contact, and contact time. There was a critical speed of population mixing beyond which the conversion rate of susceptible nondrinkers was saturated, and the bar both enhanced and buffered the rate of propagation, changing the model dynamics. CONCLUSIONS: The models demonstrate that the basic dynamics underlying social influences on drinking behavior are shaped by contacts between drinkers and focused by characteristics of drinking environments.
OBJECTIVES: We developed a preliminary agent-based simulation model designed to examine agent-environment interactions that support the development and maintenance of drinking behavior at the population level. METHODS: The model was defined on a 1-dimensional lattice along which agents might move left or right in single steps at each iteration. Agents could exchange information about their drinking with each other. In the second generation of the model, a "bar" was added to the lattice to attract drinkers. RESULTS: The model showed that changes in drinking status propagated through the agent population as a function of probabilities of conversion, rates of contact, and contact time. There was a critical speed of population mixing beyond which the conversion rate of susceptible nondrinkers was saturated, and the bar both enhanced and buffered the rate of propagation, changing the model dynamics. CONCLUSIONS: The models demonstrate that the basic dynamics underlying social influences on drinking behavior are shaped by contacts between drinkers and focused by characteristics of drinking environments.
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