Can J Infect Dis Med Microbiol Vol 26 No 1 January/February 2015 23
Bibliographic record
Abstract
2015;26(1):23-29. BACKGROUND: Recent trials report the efficacy of continuous tenofovir-based pre-exposure prophylaxis (PrEP) for prevention of HIV infection. The cost effectiveness of ‘on demand ’ PrEP for non-injection drug-using men who have sex with men at high risk of HIV acquisition has not been evaluated. OBJECTIVE: To conduct an economic evaluation of the societal costs of HIV in Canada and evaluate the potential benefits of this PrEP strategy. METHODS: Direct HIV costs comprised outpatient, inpatient and emergency department costs, psychosocial costs and antiretroviral costs. Resource consumption estimates were derived from the Centre Hospitalier de l’Université de Montréal HIV cohort. Estimates of indirect costs included employment rate and work absenteeism. Costs for ‘on demand ’ PrEP were modelled after an ongoing clinical trial. Cost-effectiveness analysis compared costs of ‘on demand ’ PrEP to prevent one infection with lifetime costs of one HIV infection. Benefits were presented in terms of life-years and quality-adjusted life-years. RESULTS: The average annual direct cost of one HIV infection was $16,109 in the least expensive antiretroviral regimen scenario and $24,056 in the most expensive scenario. The total indirect cost was $11,550 per year. Total costs for the first year of HIV infection ranged from $27,410 to $35,358. Undiscounted lifetime costs ranged from $1,439,984 ($662,295 discounted at 3 % and $448,901 at 5%) to $1,482,502 ($690,075 at 3 % and $485,806 at 5%). The annual cost of PrEP was $12,001 per participant, and $621,390 per infection pre-vented. The PrEP strategy was cost-saving in all scenarios for undis-counted and 3 % discounting rates. At 5 % discounting rates, the strategy is largely cost-effective: according to least and most expensive scenarios, incremental cost-effectiveness ratios ranged from $60,311 to $47,407 per quality-adjusted life-year. CONCLUSION: This ‘on demand ’ PrEP strategy ranges from cost-saving to largely cost-effective. The authors believe it represents an important public health strategy for the prevention of HIV transmission.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.062 | 0.043 |
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".