Enhanced Efficiency of Female-to-Male HIV Transmission in Core Groups in Developing Countries
Bibliographic record
Abstract
BACKGROUND: The spread of heterosexual HIV in developing countries is heterogeneous. Factors that explain the wide diversity of HIV prevalences in different countries are undetermined. International aid organizations currently appear to be focusing activities mainly on women rather than on men. GOAL: To identify critical determinants contributing to the high rates of heterosexual HIV transmission in developing countries through a review of studies investigating HIV per-act transmission rates, and to discuss how these factors might be prioritized through HIV-prevention interventions. STUDY DESIGN: Studies investigating the per-act HIV transmission rate were identified through a MEDLINE search and a review of the abstracts of the Annual International AIDS Conferences. RESULTS: When the summary mean per-act HIV transmission rates were calculated, the ratio of female-to-male HIV transmission in developing countries compared with that in the developed world was 341, whereas that for male-to-female transmission was 2.9. CONCLUSION: Enhanced female-to-male HIV transmission in male core groups is a critical determinant of high-prevalence HIV epidemics among heterosexuals in developing countries. In addition to condom promotion, there is a need for an increased emphasis on HIV-prevention activities in men to decrease their susceptibility in developing countries, particularly in the countries most affected by the epidemic.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".