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Building a Microsimulation Model of Heroin Use Careers in Australia

Author

Listed:
  • Alison Ritter

    (Drug Policy Modelling Program, National Drug and Alcohol Research Centre, University of New South Wales, NSW, Australia 2052)

  • Nagesh Shukla

    (SMART Infrastructure Facility, University of Wollongong, NSW, Australia 2522)

  • Marian Shanahan

    (Drug Policy Modelling Program, National Drug and Alcohol Research Centre, University of New South Wales, NSW, Australia 2052)

  • Phuong Van Hoang

    (Drug Policy Modelling Program, National Drug and Alcohol Research Centre, University of New South Wales, NSW, Australia 2052)

  • Vu Lam Cao

    (SMART Infrastructure Facility, University of Wollongong, NSW, Australia 2522)

  • Pascal Perez

    (SMART Infrastructure Facility, University of Wollongong, NSW, Australia 2522)

  • Michael Farrell

    (National Drug and Alcohol Research Centre, University of New South Wales, NSW, Australia 2052)

Abstract

Illicit heroin use is a worldwide problem, with significant health and social costs. Treatment is known to be effective in changing heroin use habits, but it often needs to be provided over a lifetime, with people cycling in and out of treatment. It is therefore important to capture a long-term perspective on heroin use careers. The aim of this project was to build a lifetime microsimulation model of heroin using careers. This paper describes the conceptual logic of the model, the input parameters and the verification and validation results. A microsimulation model was chosen as the most appropriate simulation platform with 9 states, and 111,400 individuals (aged between 18 and 60) each with gender, HIV (human immunodeficiency virus) and HCV (hepatitis C) status, and treatment history. Probabilities associated with crime commission and individually calculated lengths of stay in each state were determined from multiple datasets. The model included costs associated with treatment provision, healthcare services, criminal activity, life years lost, and family benefit of treatment. The final model represented 42 years of a heroin use career for a cohort based on Australian (New South Wales) data. Individuals cycle into and out of heroin using states (including abstinence), as well as treatment and prison states. We were able to build a stable, tractable model and verified all parameters. Validation against external data sources revealed high validity. While there are limitations associated with any model, the heroin career model now has the potential to be used for simulations of alternate policy scenarios.

Suggested Citation

  • Alison Ritter & Nagesh Shukla & Marian Shanahan & Phuong Van Hoang & Vu Lam Cao & Pascal Perez & Michael Farrell, 2016. "Building a Microsimulation Model of Heroin Use Careers in Australia," International Journal of Microsimulation, International Microsimulation Association, vol. 9(3), pages 140-176.
  • Handle: RePEc:ijm:journl:v:9:y:2016:i:3:p:140-176
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    References listed on IDEAS

    as
    1. Price, R.K. & Risk, N.K. & Spitznagel, E.L., 2001. "Remission from drug abuse over a 25-year period: Patterns of remission and treatment use," American Journal of Public Health, American Public Health Association, vol. 91(7), pages 1107-1113.
    2. Gary A. Zarkin & Alexander J. Cowell & Katherine A. Hicks & Michael J. Mills & Steven Belenko & Laura J. Dunlap & Kimberly A. Houser & Vince Keyes, 2012. "Benefits and costs of substance abuse treatment programs for state prison inmates: results from a lifetime simulation model," Health Economics, John Wiley & Sons, Ltd., vol. 21(6), pages 633-652, June.
    3. Gary A. Zarkin & Laura J. Dunlap & Katherine A. Hicks & Daniel Mamo, 2005. "Benefits and costs of methadone treatment: results from a lifetime simulation model," Health Economics, John Wiley & Sons, Ltd., vol. 14(11), pages 1133-1150, November.
    4. Eugenio Zucchelli & Andrew M Jones & Nigel Rice, 2012. "The evaluation of health policies through dynamic microsimulation methods," International Journal of Microsimulation, International Microsimulation Association, vol. 5(1), pages 2-20.
    5. Jonathan Karnon & James Stahl & Alan Brennan & J. Jaime Caro & Javier Mar & Jörgen Möller, 2012. "Modeling Using Discrete Event Simulation," Medical Decision Making, , vol. 32(5), pages 701-711, September.
    6. Carolyn M. Rutter & Alan M. Zaslavsky & Eric J. Feuer, 2011. "Dynamic Microsimulation Models for Health Outcomes," Medical Decision Making, , vol. 31(1), pages 10-18, January.
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    More about this item

    Keywords

    Microsimulation model; heroin; opioids; lifetime model;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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