Back to Annual Meeting Page		American Public Health Association 133rd Annual Meeting & Exposition December 10-14, 2005 Philadelphia, PA

Abstract #120707

Dennis M. Gorman, PhD, Department of Epidemiology & Biostatistics, School of Rural Public Health, Texas A&M Health Science Center, 3000 Briarcrest Drive, Suite 310, Bryan, TX 77802, 979-458-2236, gorman@srph.tamhsc.edu, Jadranka Mezic, MS, Aimdyn, Inc., 1226 1/2 State Street, Santa Barbara, CA 93101, Igor Mezic, PhD, Department of Mechanical & Environmental Engineering, University of California, Engineering II Bldg., Room 2355, Santa Barbara, CA 93106-5070, and Paul J. Gruenewald, PhD, Prevention Research Center, 1995 University Ave, Suite 450, Berkeley, CA 94704.

Objectives. Agent-based modeling and other computer-based simulations have been increasingly used since the 1990s in the social sciences as a means of understanding social processes and dynamics. This approach has proved especially useful in understanding complex social dynamics, notably those involving interactions between micro and macro processes and the development of emergent behaviors. This study presents an 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 one-dimensional lattice along which agents might move left or right in single steps at each iteration. In line with current literature on the dynamics of drinking behavior, three types of agents were included: susceptible non-drinkers, current drinkers and former drinkers (and these were considered to be classes or groups that do not have fixed, long-term memberships). Agents could exchange information about their drinking with one another and, in the second generation of the model, drinkers were attracted to a certain location (a “bar”). 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 susceptible conversion rate 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.

Learning Objectives:

• Describe and assess the potential uses and applications of mathematical models and especially agent-based models to the understandinfg of public health problems
• Assess the application of agent-based modeling to an area of reaserch (alcohol studies) in which emergent behavior and person-environment interactions are of central importance

Keywords: Alcohol Use, System Involvement

Presenting author's disclosure statement:

I wish to disclose that I have NO financial interests or other relationship with the manufactures of commercial products, suppliers of commercial services or commercial supporters.