Simulating patterns of heroin addiction within the social context of a local heroin market
This study illustrates how the social structure of the heroin market can impact the physiology of heroin addiction and how heterogeneity of addiction patterns can be shaped by market dynamics. We use a novel agent-based modeling (ABM) approach to simulate possible neurophysiologic functions based on the collective self-organizing behavior of market agents. The conceptual model is based on three components: biological, behavioral, and social. Biological components are informed by mechanistic animal studies, behavioral component relies on studies of real-life human experiences with addiction, and social aspects are based on market research that describes the transactional and decision-making processes associated with the distribution of drugs within local drug markets. Using ABM, this paper unifies these three components to simulate how heroin addiction patterns are generated and shaped through heroin markets. The market model is based on data from an ethnographic study of a local heroin market and includes customers (users), street and private dealers, street brokers, police, and other potential market actors. Behavioral data is based on converting narrative descriptions and fieldwork observations into formal states and transitions, and a simple model of addiction process for the drug users is based on published peer-reviewed literature. Analysis of model-based simulations reveals “binge/crash,” “stepped,” and “stable” patterns in customer addiction levels.
Hoffer, L., Bobashev, G., & Morris, R. (2012). Simulating patterns of heroin addiction within the social context of a local heroin market. In B. Gutkin, & SH. Ahmed (Eds.), Computational Neuroscience of Drug Addiction (pp. 313-331). New York, NY: Springer. DOI: 10.1007/978-1-4614-0751-5_11