Dynamics and Control of Illicit Drug Consumption

01.09.2000 - 01.09.2004
Forschungsförderungsprojekt
Illicit drugs create substantial problems for many countries and present difficult management challenges. At the strategic level, drug policy can be viewed as a resource allocation problem: How should scarce resources be divided among competing drug control programs? This topic has received considerable attention, but until recently the answers have been static, finding that one intervention is so and so much more effective than another intervention, without qualification as to the stage of the drug epidemic. But drug problems are dynamic, evolving over time with significant feedback effects. Thus, one might expect the optimal mix of drug control interventions to vary over time. Research conducted in this project focused on several different managerial questions. For instance, we investigated how the relative effectiveness of different types of prevention varies over the course of a drug epidemic; we studied optimal spending for drug substitution programmes in the context of a dynamic "epidemic" model of both drug use and drug-use related infections like hepatitis C or HIV; or, we extended traditional single- and multi-state dynamic models by explicitly considering the age distribution of users. The results obtained have had a significant effect on policy makers¿ thinking in consumer countries, even in such distant places as Australia. Methodologically, they illustrate the benefits of combining optimal control theory with innovative modeling to address practical management problems that otherwise could not be described let alone analysed within a rigorous mathematical framework. This project has stimulated parallel research innovation in other domains, including non-drug related crime, the control of the spread of infectious diseases including HIV and HCV, counter-terror, and, interestingly, marketing of legal goods. It has also led to methodological advances, notably pertaining to multiple equilibria and so-called DNS curves, as well as novel solution techniques for age-structured control systems (including their implementation on computers for numerical solution).

Personen

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Subprojektleiter_in

Institut

Grant funds

  • FWF - Österr. Wissenschaftsfonds (National) Austrian Science Fund (FWF)

Schlagwörter

DeutschEnglisch
DrogenepidemieDrug Epidemics
Praevention, Therapie, PolizeiPrevention, Treatment, Law Enforcement
Dynamische Kosten-Nutzen-AnalyseDynamic Cost-Benefit Analysis
Optimale Kontrolle & Dynamische SpieleOptimal Control & Dynamic Games
MehrzustandsmodelleMulti-State Models
Soziales NetzwerkSocial Network

Publikationen