title: SimAmph: an agent-based simulation model for exploring the use of psychostimulants and related harm amongst young Australians.
abstract: BACKGROUND
  Computer simulations provide a useful tool for bringing together diverse sources of information in order to increase understanding of the complex aetiology of drug use and related harm, and to inform the development of effective policies. In this paper, we describe SimAmph, an agent-based simulation model for exploring how individual perceptions, peer influences and subcultural settings shape the use of psychostimulants and related harm amongst young Australians.
  
  
  METHODS
  We present the conceptual architecture underpinning SimAmph, the assumptions we made in building it, the outcomes of sensitivity analysis of key model parameters and the results obtained when we modelled a baseline scenario.
  
  
  RESULTS
  SimAmph's core behavioural algorithm is able to produce social patterns of partying and recreational drug use that approximate those found in an Australian national population survey. We also discuss the limitations involved in running closed-system simulations and how the model could be refined to include the social, as well as health, consequences of drug use.
  
  
  CONCLUSIONS
  SimAmph provides a useful tool for integrating diverse data and exploring drug policy scenarios. Its integrated approach goes some way towards overcoming the compartmentalisation that characterises existing data, and its structure, parameters and values can be modified as new data and understandings emerge. In a companion paper (Dray et al., 2011), we use the model outlined here to explore the possible consequences of two policy scenarios.
authors.affiliation: SMART Infrastructure Facility, University of Wollongong, Wollongong, NSW 2522, Australia.
authors.forename: Pascal
authors.initials: P
authors.lastname: Perez
authors.forename: Anne
authors.initials: A
authors.lastname: Dray
authors.forename: David
authors.initials: D
authors.lastname: Moore
authors.forename: Paul
authors.initials: P
authors.lastname: Dietze
authors.forename: Gabriele
authors.initials: G
authors.lastname: Bammer
authors.forename: Rebecca
authors.initials: R
authors.lastname: Jenkinson
authors.forename: Christine
authors.initials: C
authors.lastname: Siokou
authors.forename: Rachael
authors.initials: R
authors.lastname: Green
authors.forename: Susan L
authors.initials: SL
authors.lastname: Hudson
authors.forename: Lisa
authors.initials: L
authors.lastname: Maher
mesh_terms: D000328:Adult; D000367:Age Factors; D001315:Australia / Q000453:epidemiology; D000697:Central Nervous System Stimulants / Q000008:administration & dosage* / Q000191:economics / Q000633:toxicity*; D003198:Computer Simulation; D003430:Cross-Sectional Studies; D004335:Drug and Narcotic Control; D005221:Fatigue / Q000453:epidemiology / Q000209:etiology; D006306:Health Surveys; D006801:Humans; D033183:Interdisciplinary Communication; D007398:Interpersonal Relations; D018803:Models, Economic; D008960:Models, Psychological; D010379:Peer Group; D015995:Prevalence; D011618:Psychotic Disorders / Q000453:epidemiology / Q000209:etiology; D012307:Risk Factors; D019966:Substance-Related Disorders / Q000208:ethnology / Q000503:physiopathology / Q000517:prevention & control / Q000523:psychology*; D055815:Young Adult
chemical_list: D000697:Central Nervous System Stimulants