Predictors of HIV prevalence among street-based female sex workers in Andhra Pradesh state of India: a district-level analysis
Bibliographic record
Abstract
BACKGROUND: A decline in HIV prevalence among female sex workers (FSWs) has been reported from the Indian state of Andhra Pradesh between the two rounds of integrated biological and behavioural assessment (IBBA) surveys in 2005-06 and 2009, the first of these around the time of start of the Avahan HIV prevention intervention. In order to facilitate further planning of FSW interventions, we report the factors associated with HIV prevalence among street-based FSWs. METHODS: Behavioural data from the two rounds of IBBA surveys, district-level FSW HIV prevention program data, and urbanisation data from the Census of India were utilized. A multilevel logistic model was used to investigate factors associated with inter-district variations in HIV positivity among street-based FSWs in the districts by fitting a two-level model. RESULTS: The estimated HIV prevalence among street-based FSWs changed from 16% (95% confidence interval [CI] 14.2 - 17.7%) to 12.9% (95% CI 11.5 - 14.2%) from 2005-06 to 2009. HIV positivity was significantly higher in districts with a high proportion of FSWs registered with targeted interventions (odds ratio [OR] 2.02; 95% CI 1.18-3.45), and in districts with medium (OR 2.54; 95% CI 1.58-4.08) or high (OR 1.55; 95% CI 1.05-2.29) proportion of urban population. Districts which had met the condom requirement targets for FSWs had significantly lower HIV positivity (OR 0.50; 95% CI 0.26-0.97). In round 2 survey, the districts with medium level urbanisation had significantly higher proportion of FSWs registered with HIV intervention programmes and also reported higher consistent condom use with regular partner (p < 0.001). CONCLUSIONS: Variations in HIV positivity among street-based FSWs were seen at the district level in relation to HIV intervention programs and the degree of urbanization. These findings could be used to enhance program planning to further reduce HIV transmission in this population.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 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".