Rates and determinants of HIV-attributable mortality among rural female sex workers in Northern Karnataka, India
Bibliographic record
Abstract
Female sex workers (FSWs) have among the highest rates of HIV infection in India. However, little is known about their HIV-specific mortality rates. In total, 1561 FSWs participated in a cohort study in Karnataka. Outcome data (mortality) were available on 1559 women after 15 months of follow-up. To gather details on deaths, verbal autopsy (VA) questionnaires were administered to key informants. Two physicians reviewed the VA reports and assigned underlying causes of death. Forty-seven deaths were reported during the follow-up (overall mortality rate was 2.44 per 100 person-years), with VA data available on 45 women. Thirty-five (75.6%) of these women were known to be HIV-positive, but only 42.5% were on antiretroviral therapy (ART). Forty deaths were assessed to be HIV-related, for an HIV-attributable mortality rate of 2.11 deaths per 100 person-years. Absence of a current regular partner (incidence rate ratio: 2.79; 95% confidence interval [CI]: 1.39-5.60) and older age (1.06; 1.01-1.11) were associated with increased HIV-attributable mortality. Reported duration in sex work was not related to HIV-attributable mortality. We found a high HIV-related mortality rate among this cohort of FSWs; nearly 10 times that of national mortality rates among women of a similar age group. Older age, but not reported duration in sex work, was associated with increased mortality, and suggests HIV acquisition prior to self-reported initiation into sex work. Despite significant efforts, there remain considerable gaps in HIV prevention near or before entry into sex work, as well as access and uptake of HIV treatment among FSWs.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".