Generating new evidence is not enough. DPMP is investigating ways to get evidence to policy makers. To do this DPMP is concentrating on the use of models to aid decision-making. Models, or simulations, can show policy makers the potential consequences of different choices. The models utilised by DPMP are particularly useful for exploring 'what if' scenarios.
The DPMP models are largely based on a systems perspective. This integrated systems approach allows us to explore the four streams as they dynamically interact.
Translating research evidence involves DPMP working directly with policy makers to assist in developing innovative responses to current policy problems.
Interactive modelling platform for drug policy problems
Research team: Pascal Perez, Anne Dray (HEMA) and Bohdan Durnota (Tjurunga Research)
Overview: Having developed the agent-based model called SimDrug in Stage One of DPMP, and conducted further policy simulations around policing as represented in SimDrugPolicing and SimHero the modelling team has now begun to use the models in practice with policy makers. These projects focus on developing policy relevant tools for exploring options. The development and implementation of the model is based on collective design principles whereby a group of experts (field researchers, modellers and practitioners) contribute iteratively to the creation process. In the process of developing the model, stakeholders participate in the process, reflecting on available data, notions of the system structure and function. This process can produce new insights and information about data gaps. The model itself, once constructed, can then be used to test various policy scenarios that are of direct interest to the policy makers.
Aside from the field work described in separate projects as noted above, the modelling team has continued developing its hardware and software. The current Beta version of our Multi-Agent Based Simulation (MABS) platform is implemented in Java, using the Open Source software RePAST. The modelling platform can be either deployed as a Virtual Machine on independent computers or directly accessed through the internet (interactive portal). Issues related to the dynamical links with Google-Map are being addressed and we have developed procedures for users to populate the maps with sites of interest: hospitals, police stations, residential treatment centres. Charts & plots menus have been added as well. In this way, the user-interface for DPMP models is being progressively upgraded.
More information: pascal.perez@anu.edu.au
Assessing the economic consequences of cannabis policy options
Research team: Marian Shanahan, Rachel Ngui and Alison Ritter (NDARC)
Advisors: Rosalie Pacula (RAND), Wendy Swift and Maree Teesson (NDARC)
Overview:Aims: The aims of this project are to estimate the costs and benefits of two alternate cannabis policies relative to the existing cannabis policy in NSW, Australia. Changes to the status of cannabis, ranging from legalisation through to tougher enforcement of prohibition are frequently posed. To date, the debate has primarily centred on arguments associated with liberty and harms, but not the economic implications. This research takes an economics perspective and examines the question of the relative costs and benefits of different cannabis policy options.
In the context of the NSW context and environment, and other cannabis policies such as treatment, prevention and so on the three policies being compared are:
- Cannabis Cautioning Scheme as represented by the current (as of 2007) NSW policies
- Civil Infringement Scheme similar to that which exists in Western Australia; and
- A regulated and legalised framework
Methods: Using a static economic model, the costs and benefits will be estimated from a societal perspective and will include the health sector, the criminal justice sector, and impacts on education and productivity as well as on the individual. Various tools such as willingness to pay, discrete choice experiments, and quality-of-life measures will be used to assess the intangible outcomes from policy changes.
Data: The data for this project will come from a wide variety of sources, crime statistics, survey of police activities, household survey data, drug treatment data and the literature.
Expected completion date: December 2010
This research forms part of the Drug Policy Modelling Program and is funded jointly through an ARC Discovery Grant (DP0880066) and by the Colonial Foundation Trust.
More information: m.shanahan@unsw.edu.au
Examining the relative cost effectiveness of different types of law enforcement interventions directed towards methamphetamine
Research team: Alison Ritter, David Bright, Wendy Gong, Jenny Chalmers and Caitlin Hughes (NDARC)
Overview:Law enforcement interventions against methamphetamine can occur at any level of the supply chain:
- End product manufacture off-shore
- Precursor importation
- End product importation
- Domestic precursor attainment
- Domestic manufacture
- Domestic distribution
Where should law enforcement invest its resources? This project aims to both detail the methamphetamine supply chains and assess the returns on investment for law enforcement. The project is a macro-level analysis that will provide comparisons of the economic consequences of law enforcement on criminals and criminal networks at each level of the supply chain. The research will be conducted in two parts: (1) a detailed description of methamphetamine supply chains, and (2) modelling the economic consequences of different law enforcement interventions. Data for the first part of the project will be sourced from published and grey literature, judges’ comments in methamphetamine cases, interviews with key informants (KIs) from policing, and interviews with incarcerated offenders who have knowledge of methamphetamine importation, manufacture, or high level distribution.
Expected completion date: December 2009
More information: david.bright@unsw.edu.au
Support for Phase 2 of the evaluation of the Cannabis Infringement Notice Scheme in Western Australia
Research team: Simon Lenton (National Drug Research Institute)
Overview: This project provides part funding for the analysis, report writing and dissemination of two sub-studies from the Evaluation of the Cannabis Infringement Notice (CIN) Scheme in Western Australia which is being conducted by the National Drug Research Institute by a team led by Professor Simon Lenton. Under the CIN scheme, which became law in March 2004, adults caught in possession of up to 30 grams of cannabis, up to 2 non-hydroponic cannabis plants, or a used smoking implement, are eligible for an infringement notice whereby if they pay the fine of between $100 and $200 dollars, or attend an education session, they can avoid a criminal conviction. Data collection for NDRI's pre-post evaluation began in 2002 and the post phase was completed in 2006-07. It involves public attitude surveys, along with studies of regular cannabis users and school students, which are the focus of the current project. The project will be relevant for future cannabis law reforms in Australia and internationally. Importantly, the DPMP funding will support briefings and presentations of the results of the evaluation to policy makers here and overseas.
More information: S.Lenton@curtin.edu.au
SimDrugPolicing: An adaptation of SimDrug to explore three policing scenarios
Research team: Anne Dray, Pascal Perez (HEMA) Lorraine Mazerolle (Griffith University) and Alison Ritter (NDARC)
Overview: This project entailed adaptation of the original SimDrug model (see Monograph No. 11) to a new agent-based model called SimDrugPolicing specifically designed to explore the relative impact of three law enforcement strategies – standard patrol, hot-spot policing and problem-oriented policing - on an archetypal street-based illicit drug market. The model included users, dealers, wholesalers, outreach workers and police forces. We examined the effectiveness of each law enforcement strategy by analysing several indicators such as the number of committed crimes, dealers’ and users’ cash, overdoses and fatal overdoses. Our results show that problem-oriented policing is the most effective approach to disrupting street level drug markets in a simulated urban environment. We considered the random patrol strategy as a control scenario (nil effect hypothesis) against which the degree of effectiveness of the two other strategies can be compared. This assumption is consistent with conclusions from law enforcement experts who consider random street patrols as highly inefficient to fight drug-related crimes. The results of our simulation show that the random patrol strategy performs very poorly against our evaluation indicators including sustained high level of crimes committed by users, low probabilities of arrest, high profitability for dealers and the creation of two dense drug hotspots. By comparison, the hotspot strategy simulates the importance of crime analysis in policing, helping police to focus their law enforcement resources in high-risk areas. This scenario significantly increases the number of arrested dealers and decreases the number of crimes. Our results show that the hotspot strategy is the most effective at deterring users from criminal intentions (aborted crimes). However, it has no impact on harm reduction (total and fatal overdoses) or treatment indicators. These findings partly support our initial selection of an open system based simulation for SimDrugPolicing where the replacement of removed dealers and users at each time step limits the long-term benefits of the hotspot strategy. We acknowledge, however, that reality is much more complex than the mechanistic process presented in our simulated model. The problem-oriented policing strategy relies on concerted efforts between constables and outreach workers. This collaboration considerably increases the impact of police interventions across all selected indicators. As expected, this scenario drastically increases the number of treated users. Finally, the problem-oriented policing strategy proves to be the best at reducing the availability of drugs in the streets.
These results are consistent with a growing body of empirical support for the effectiveness of problem-oriented policing approaches in reducing crime, disorder and fear. The results have been published as a peer review book chapter (Dray A., Mazerolle L., Perez P., Ritter A. (2008). Drug Law Enforcement in an Agent-Based Model: Understanding the Dynamics of Street Level Heroin Markets. In: Lin Liu and John Eck (Eds), Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems. IGI Global, Information Science Reference, London, UK, pp 352-371).
Completed: July 2007
More information: alison.ritter@unsw.edu.au
SimHero: Policing Australia’s ‘heroin drought’: Using an agent-based model to simulate alternative outcomes
Research team: Pascal Perez, Anne Dray (HEMA), Lorraine Mazerolle (Griffith University) and Alison Ritter (NDARC)
Overview: This research built on SimDrug and SimDrugPolicing to examine how street-level drug markets adapt to a macro-level disruption to the supply of heroin, under three experimental conditions of street-level drug law enforcement: random patrol, hot spot policing and problem-oriented policing. We utilize an agent-based model to explore the relative impact of abstractions of these three law enforcement strategies after simulating an “external shock” to the supply of heroin to the street-level drug market. We use three years of data that includes the period of the “heroin drought” in Melbourne (Australia) which commenced in late 2000 and early 2001 to measure changes in a selected range of crime and harm indicators under the three policing conditions. Our results show that macro-level drug supply disruptions have a limited impact on street-level market dynamics when there is a ready replacement drug. By contrast, street-level police interventions are shown to vary in their capacity to alter drug market dynamics. Importantly, our laboratory abstraction of problem-oriented policing is shown to be the optimal strategy to disrupt street-level injecting drug markets, reduce crimes and minimize harms, regardless of the type of drug supplied to the market.
Our article describing SimHero received its final acceptance by the Journal of Experimental Criminology in March 2008.
More information: alison.ritter@unsw.edu.au
A bibliography of prison-based drug treatment
Research team: Alison Ritter and Francis Matthew-Simmons (NDARC)
Overview: One way that the DPMP contributes to improved Australian drug policy is through providing access to research evidence. We have prepared an annotated bibliography of relevant research in relation to prison-based drug treatment. This was originally prepared for the ACT to enable them to base their drug treatment services in the new prisons on best practice principles and current research evidence. The annotated bibliography focussed on Australian research but also included much international work. Only research papers that reported treatment in prison settings were included. More than 200 papers were located – the majority (96) are Australian, followed by 59 from the USA, and 40 from European countries. The bibliography is divided into a number of sections including therapeutic communities literature; pharmacotherapies literature; needle syringe programs literature; throughcare/aftercare literature; drug testing literature; and program descriptions. Wherever possible we provided an Abstract and a link to the reference.
More information: alison.ritter@unsw.edu.au
Completed: December 2008
Click here to access the bibliography.
Cannabis Diversion Model
Research team: Caitlin Hughes and Alison Ritter (NDARC)
Consultant: Jennifer Badham (Critical Connections)
Overview: Drug diversion has become a popular policy intervention used for responding to illicit drug users in Australia. Much of the drug diversion programs focus on cannabis, a drug used by 33% Australians (Australian Institute of Health and Welfare, 2008) and that accounts for 74% illicit drug offences (Australian Crime Commission 2006). Drug diversion aims to reduce future drug use (through educating and/or treating drug use), increase the efficiency of the criminal justice system and reduce the costs of responding to drug use. Yet there is limited understanding to date on how to improve the designs of drug diversion systems and to facilitate the best possible outcomes.
This project builds a system dynamics model of cannabis diversion in Australia. It includes all existing responses to cannabis users, through both cannabis diversion and traditional court responses and models their impacts on future crime and the cost to the criminal justice system. In so doing it provides a tool to aid consideration of plausible policy scenarios: what would be the impact of changing the number of cannabis users diverted, the type of programs used, improving the effectiveness of cannabis interventions or removing breach conditions for diversion programs? What types of changes would be most cost-effective? This will enhance the capacity for evidence-based decisions on the design of Australian cannabis diversion systems.
Completed: December 2008
More information: caitlin.hughes@unsw.edu.au
Opioid Pharmacotherapy Review
Research team: Alison Ritter and Jenny Chalmers (NDARC)
Consultants: Geoff McDonnell (UNSW) and Mark Heffernan (Evans & Peck)
Advisory group: Nick Lintzeris, Alex Wodak, Richard Mattick, Bob Batey, Tamara Speed
Overview: The Australian National Council on Drugs (ANCD) commissioned the Drug Policy Modelling Program to undertake a project to determine whether the availability, accessibility and affordability of Australia’s pharmacotherapy programs for the treatment of opioid dependence meet demand. The project has been conducted in two parts:
- a qualitative review of the issues associated with the Australian pharmacotherapy program; and
- the development of a simulation model, in this case a system dynamics model, of the pharmacotherapy service system that could be used as a tool for policy makers exploring policy options around several issues of concern: dispensing fees, availability of treatment places, potential increases in the population of opioid dependent people and the quality of treatment services.
Completed: May 2009
More information:
j.chalmers@unsw.edu.au
Optimal allocation of treatment for hepatitis C virus among injecting drug users in and out of methadone maintenance treatment
Research team: Irmgard Zeiler (University of Technology, Vienna), Trevor Langlands, John Murray (UNSW) and Alison Ritter (NDARC)
Overview:
Background: This aim of this work was to use mathematical modelling to explore and draw some conclusions about effective policy for hepatitis C virus (HCV) treatment in Australia in the context of methadone maintenance treatment (MMT).
Method: We consider two mathematical models to depict HCV in the population of injecting drug users (IDU) within Australia. The first model considers the IDU population as a whole. The second model includes separate components for those that are or are not enrolled in MMT. The impact of different levels of HCV treatment and its allocation dependent on MMT status were then determined in terms of the steady state levels of each of these models.
Results: Although increasing levels of HCV treatment decrease chronic infection prevalence, initially numbers of acutely infected can rise. This is caused by the high rate of reinfection that also significantly slows down the time to achieve lower HCV prevalence. We find that no matter the extent of HCV treatment, HCV prevalence cannot be eliminated without limiting risk behaviour. At current rates of turnover of individuals in MMT, over 84% of HCV therapy should be allocated to those not in MMT.
Conclusions: Contrary to generally held beliefs regarding HCV treatment the majority of therapy should be allocated to those that are still actively injecting. This is due to rates of reinfection and to the high turnover rate of individuals in MMT. Our results also highlight the necessity to constrain risk behaviour with any expansion of HCV treatment.
Copy of paper available on request.
Completed: September 2009
More information:
alison.ritter@unsw.edu.au