The future role of rectal and vaginal microbicides to prevent HIV infection in heterosexual populations: implications for product development and prevention
Bibliographic record
Abstract
OBJECTIVES: To compare the potential impact of rectal (RMB), vaginal (VMB) and bi-compartment (RVMB) (applied vaginally and protective during vaginal and anal intercourse) microbicides to prevent HIV in various heterosexual populations. To understand when a RMB is as useful than a VMB for women practicing anal intercourse (AI). METHODS: Mathematical model was used to assess the population-level impact (cumulative fraction of new HIV infections prevented (CFP)) of the three different microbicides in various intervention scenarios and prevalence settings. We derived the break-even RMB efficacy required to reduce a female's cumulative risk of HIV infection by the same amount than a VMB. RESULTS: Under optimistic coverage (fast roll-out, 100% uptake), a 50% efficacious VMB used in 75% of sex acts in population without AI may prevent ∼33% (27, 42%) new total (men and women combined) HIV infections over 25 years. The 25-year CFP reduces to ∼25% (20, 32%) and 17% (13, 23%) if uptake decreases to 75% and 50%, respectively. Similar loss of impact (by 25%-50%) is observed if the same VMB is introduced in populations with 5%-10% AI and for RR(RAI)=4-20. A RMB is as useful as a VMB (ie, break-even) in populations with 5% AI if RR(RAI)=20 and in populations with 15%-20% AI if RR(RAI)=4, independently of adherence as long as it is the same with both products. The 10-year CFP with a RVMB is twofold larger than for a VMB or RMB when AI=10% and RR(RAI)=10. CONCLUSIONS: Even low AI frequency can compromise the impact of VMB interventions. RMB and RVMB will be important prevention tools for heterosexual populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".