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Extending drug ethno-epidemiology using agent-based modelling.

Moore D, Dray A, Green R, Hudson SL, Jenkinson R, Siokou C, Perez P, Bammer G, Maher L, Dietze P

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  • Journal Addiction (Abingdon, England)

  • Published 05 Oct 2009

  • Volume 104

  • ISSUE 12

  • Pagination 1991-7

  • DOI 10.1111/j.1360-0443.2009.02709.x

Abstract

To show how the inclusion of agent-based modelling improved the integration of ethno-epidemiological data in a study of psychostimulant use and related harms among young Australians.

Agent-based modelling, ethnographic fieldwork, in-depth interviews and epidemiological surveys.

Melbourne, Perth and Sydney, Australia.

Club drug users in Melbourne, recreational drug users in Perth and street-based injecting drug users in Sydney. Participants were aged 18-30 years and reported monthly or more frequent psychostimulant use.

Agent-based modelling provided a specific focus for structured discussion about integrating ethnographic and epidemiological methods and data. The modelling process was underpinned by collective and incremental design principles, and produced 'SimAmph', a data-driven model of social and environmental agents and the relationships between them. Using SimAmph, we were able to test the probable impact of ecstasy pill-testing on the prevalence of harms--a potentially important tool for policy development. The study also navigated a range of challenges, including the need to manage epistemological differences, changes in the collective design process and modelling focus, the differences between injecting and non-injecting samples and concerns over the dissemination of modelling outcomes.

Agent-based modelling was used to integrate ethno-epidemiological data on psychostimulant use, and to test the probable impact of a specific intervention on the prevalence of drug-related harms. It also established a framework for collaboration between research disciplines that emphasizes the synthesis of diverse data types in order to generate new knowledge relevant to the reduction of drug-related harms.