HIV incidence from the first population-based cohort study in India
Bibliographic record
Abstract
BACKGROUND: Understanding about who acquires new HIV infection and the determinants of why some persons get infected and others do not is fundamental to controlling HIV in the population. We assess HIV incidence and its associations in the population of a high HIV burden district in Andhra Pradesh state in southern India by a population-based longitudinal cohort study. METHODS: We re-surveyed a population-based cohort of 12,617 adults in Guntur district of Andhra Pradesh for which we had reported a baseline HIV prevalence of 1.72% (rural 1.64%, urban 1.89%) among the 15-49 years age group in 2004-2005. We conducted interviews to assess risk behaviour and performed HIV testing again in 2010-2011. We assessed the rate of new HIV infection and its associations using multiple logistic regression. RESULTS: The participation rate in the follow-up was 74.9% and 63.9% of the baseline rural and urban samples, respectively. Over a mean follow-up of 5.63 years, the incidence of HIV was 1.26 per 1000 person-years (95% CI 0.83-1.69), after adjusting for slight compositional bias in the follow-up sample. The incidence per 1000 person-years was higher among rural men (1.68) than urban men (0.85), and among rural women (1.28) than urban women (0.54). The strongest association with incidence was a HIV positive spouse in the baseline for both men (odds ratio 266, 95% CI 62-1137) and women (odds ratio 28, 95% CI 9-88). Among men the other significant associations with HIV incidence were frequent use of condom for sex over the past 6 months, non-circumcision, more than one lifetime woman sex partner or ever visited sex worker, and transport-related occupation; for women the other significant associations were having had HIV testing other than antenatal check-up, previously married but currently not, and tobacco use. CONCLUSION: These first population-based cohort incidence data from India suggest that rural areas of high HIV burden states would need more attention to prevent new HIV infections, and that spouses of HIV positive persons and some other risk groups need to be targeted more effectively by HIV prevention programmes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 0.001 |
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".