Impact of an intensive HIV prevention programme for female sex workers on HIV prevalence among antenatal clinic attenders in Karnataka state, south India: an ecological analysis
Bibliographic record
Abstract
OBJECTIVES: To examine the impact of an intensive HIV preventive intervention (IPI) among female sex workers (FSW) on community HIV transmission, as represented by HIV prevalence among young antenatal clinic (ANC) attenders in Karnataka state, south India. METHODS: The IPI was initiated in 18 of the 27 districts in Karnataka in 2003, and was generally at scale by mid-2005, covering over 80% of the urban FSW population. We examined trends over time in HIV prevalence from annual HIV surveillance conducted among ANC attenders in Karnataka under the age of 25 years from 2003 to 2007, comparing the IPI with the other districts. RESULTS: Overall, HIV prevalence among ANC attenders under 25 years of age declined from 1.40% to 0.77%. In a multivariate model, the decline in HIV prevalence in the IPI districts compared to the other districts was statistically significant (P = 0.01), with an adjusted annual odds ratio of 0.88 (95% CI 0.79-0.97). The decline in standardized HIV prevalence in the IPI districts over the period was 56%, compared to 5% in the non-IPI districts. CONCLUSIONS: Although this analysis is limited by lack of precise comparative data on intervention coverage and intensity, it supports the notion that scaled-up, intensive, targeted HIV preventive interventions among high-risk groups can have a measurable and relatively rapid impact on HIV transmission in the general population, particularly young sexually active populations as represented by ANC attenders. Such focused intervention programmes should be rapidly taken to scale in all HIV epidemics, and especially in concentrated epidemics such as in 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".