Methadone Maintenance and HIV Prevention: A Cost-Effectiveness Analysis
Bibliographic record
Abstract
We assess the cost-effectiveness of maintenance treatment for heroin addiction, with emphasis on its role in preventing HIV infection. The analysis is based on a dynamic compartmental model of the HIV epidemic among a population of adults, ages 18 to 44. The population is divided into nine compartments according to infection status and risk group. The model takes into account disease transmission from drug injection and sexual contacts. The health benefits of methadone maintenance and the resulting HIV infections averted are measured in terms of life years gained and quality-adjusted life years gained. Costs considered include all health-care costs (including cost of HIV care and other health care) and the cost of methadone maintenance. The analysis shows that expanding existing methadone maintenance programs is a cost-effective health-care intervention that can play an important role in slowing the spread of HIV and improving the length and quality of life for injection drug users (IDUs), and that such expansion is cost-effective even in populations with low HIV prevalence among IDUs. Incremental expansion of methadone maintenance programs was found to have a cost-effectiveness ratio of between $9,700 and $17,200 per life year gained, and between $6,300 and $10,900 per quality-adjusted life year gained. Although methadone maintenance treatment is provided to IDUs, the analysis shows that significant benefits accrue to non-IDU members of the population. Sensitivity analysis shows that new methadone maintenance treatment slots will be cost-effective even if they are twice as expensive and half as effective in reducing risky behavior as current methadone maintenance programs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".