Potential impact and cost-effectiveness of oral HIV pre-exposure prophylaxis for men who have sex with men in Cotonou, Benin: a mathematical modelling study
Bibliographic record
Abstract
BACKGROUND: Oral HIV pre-exposure prophylaxis (PrEP) can effectively reduce HIV incidence. A 2020-21 demonstration project assessed the feasibility and health outcomes of offering oral PrEP to men who have sex with men (MSM) in Cotonou, Benin. We evaluated the epidemiological impact and cost-effectiveness of this project and the potential scale-up of oral HIV PrEP for MSM in Cotonou. METHODS: We calibrated an HIV transmission-dynamic model structured by age and risk within a Bayesian framework to MSM-specific HIV prevalence and treatment data, parameterised with project behavioural and cost (including PrEP drug, implementation, and HIV care costs) data. We estimated the impact and cost-effectiveness of the 2020-21 Cotonou demonstration project (PrEP coverage, 5-10% of all MSM who are not living with HIV in Grand Cotonou; and adherence, 13-21% taking at least four of seven required doses [ie, at least four doses per week for daily users and at least four of seven expected doses given reported sexual activity for on-demand users]) and of its potential scale-up over 5 years (from 2022 to 2027), reaching 30% coverage of MSM in Grand Cotonou and with demonstration project adherence levels. We additionally modelled ideal PrEP adherence (100% taking at least four of seven required doses). We estimated the percentage of cumulative new HIV infections averted among participating MSM over 1 year and among all MSM in Grand Cotonou and their female partners over 20 years, and cost-effectiveness as cost per disability-adjusted life-year (DALY) averted over 20 years. Costs and DALYs were discounted 3% annually. FINDINGS: We found that the demonstration project averted an estimated 21·5% (95% uncertainty interval 16·6 to 26·2) of HIV infections among participants over 1 year. With ideal adherence, cases that would be averted increased to 95·2% (90·8 to 98·8). A 5-year PrEP scale-up could avert 3·2% (1·6 to 4·8) of HIV infections among all MSM and female partners over 20 years, at US$388 (36 to 2792) per DALY averted. With ideal adherence, this decreased to -$28 (-126 to 589) per DALY averted. INTERPRETATION: Low adherence to PrEP restricted the impact of the demonstration project. At 30% coverage among MSM by 2027, PrEP scale-up would be cost-effective at a $1225 threshold with 86·6% probability, and it could be more cost-effective if high adherence could be reached without substantially increasing costs. FUNDING: Canadian Institutes of Health Research and US National Institutes of Health. TRANSLATION: For the French translation of the abstract see Supplementary Materials section.
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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 | 0.002 | 0.006 |
| 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 | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".