O17.1 Increased HIV Prevention Programme Coverage and Decline in HIV Prevalence Among Female Sex Workers in South India
Bibliographic record
Abstract
Objectives As one way of assessing the impact ofAvahan, the India AIDS Initiative of the Bill & Melinda Gates Foundation, we examined the association between HIV prevention programme indicators and changes in HIV prevalence among female sex workers (FSWs) between 2006 and 2010. Methods HIV prevalence among FSWs was measured in two large surveys (2006 and 2010) across 24 districts in south India (n∼11,000 per round). A random-effect multilevel logistic regression analysis was performed using HIV as the outcome, with individual independent variables (from both surveys) at level 1 and district-level FSW-specific programme indicators (from theAvahancomputerised monitoring system) and contextual variables (from Indian government datasets) at level 2. Program indicators included their 2006 value, the difference in their values between the surveys, and the interaction between the latter and study round. The analysis also controlled for baseline HIV prevalence and its interaction with study round. Results HIV prevalence among FSWs decreased from 17.0% (round 1) to 14.2% (round 2; p < 0.001). The odds ratio (OR) of the interaction term between the difference in programme coverage (% of FSWs contacted by the programme in a given year) and the survey round was 0.995 (p = 0.006), indicating that increased coverage was significantly associated with the decline in HIV prevalence between rounds. ORs comparing HIV prevalence between rounds varied with the level of increase in coverage and were statistically significant with coverage increase ≥ quartile (Q) 1: OR = 0.85 at Q1, 0.78 at Q2, 0.66 at Q3 and 0.51 at Q4. Conclusions These findings suggest that increased programme coverage was associated with declining HIV prevalence among FSWs covered by theAvahanprogramme. The triangulation of our results with those from other approaches used in evaluatingAvahansuggests a major impact of this intervention on the HIV epidemic in southern India.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".