Cost-utility Analysis of Universal Pre-exposure Prophylaxis Coverage for Men who have Sex with Men at a High Risk of Human Immunodeficiency Virus Infection in Ontario, Canada
Bibliographic record
Abstract
HIV pre-exposure prophylaxis (PrEP) was approved by Health Canada in 2016. Currently in Ontario, those under the age of 25 or aged 65 years or older can access PrEP free of charge through public drug coverage programs. This study assessed the cost-effectiveness of providing public coverage for PrEP to all high-risk Ontario MSM. A Markov cohort model was built from the perspective of the Ontario Ministry of Health and Long-Term Care (MOH) using a lifetime time horizon. Health states included HIV positive, HIV negative, and Dead. Transition probabilities, health state utilities and HIV treatment costs were sourced from published literature. Costs of HIV prevention were estimated through a micro-costing approach. HIV infection risk was estimated using the HIRI-MSM screening tool. Offering PrEP to all high-risk MSM through the Ontario MOH is dominant to current coverage circumstances due to a reduction in costly HIV infections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".