| Title |
Dynamic compartmental model of trends in Australian drug use
|
|---|---|
| Published in |
Health Care Management Science, March 2007
|
| DOI | 10.1007/s10729-007-9012-0 |
| Pubmed ID | |
| Authors |
Jonathan P. Caulkins, Paul Dietze, Alison Ritter |
| Abstract |
A five-state compartment model of trends in illicit drug use in Australia is parameterized using data from multiple sources. The model reproduces historical prevalence and supports what-if analyses under the assumption that past trajectories of drug escalation and desistance persist. For fixed initiation, the system has a unique stable equilibrium. The chief qualitative finding is that even though some users escalate rapidly, regular injection drug use still adjusts to changes in incidence with considerable inertia and delay. This has important policy implications, e.g., concerning the timing of reductions in drug-related social cost generated by interventions that reduce the social cost per injection user versus those that cut drug initiation. |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 4% |
| India | 1 | 4% |
| Unknown | 22 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 29% |
| Student > Ph. D. Student | 5 | 21% |
| Student > Master | 4 | 17% |
| Student > Bachelor | 2 | 8% |
| Student > Doctoral Student | 2 | 8% |
| Other | 1 | 4% |
| Unknown | 3 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 6 | 25% |
| Psychology | 2 | 8% |
| Nursing and Health Professions | 2 | 8% |
| Computer Science | 2 | 8% |
| Economics, Econometrics and Finance | 2 | 8% |
| Other | 6 | 25% |
| Unknown | 4 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 January 2015.
All research outputs
#7,486,330
of 22,883,326 outputs
Outputs from Health Care Management Science
#86
of 285 outputs
Outputs of similar age
#27,260
of 77,212 outputs
Outputs of similar age from Health Care Management Science
#1
of 1 outputs
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