Correlates of HIV infection among street-based and venue-based sex workers in Vietnam
Bibliographic record
Abstract
Commercial sex work is one of the driving forces of the HIV epidemic across the world. In Vietnam, although female sex workers (FSWs) carry a disproportionate burden of HIV, little is known about the risk profile and associated factors for HIV infection among this population. There is a need for large-scale research to obtain reliable and representative estimates of the measures of association. This study involved secondary data analysis of the 'HIV/STI Integrated Biological and Behavioral Surveillance' study in Vietnam in 2009-2010 to examine the correlates of HIV among FSWs. Data collected from 5298 FSWs, including 2530 street-based sex workers and 2768 venue-based sex workers from 10 provinces in Vietnam, were analyzed using descriptive statistics and bivariate and multivariate logistic regression analyses. HIV prevalence among the overall FSW population was 8.6% (n = 453). However, when stratified by FSW subpopulations, HIV prevalence was 10.6% (n = 267) for street-based sex workers and 6.7% (n = 186) for venue-based sex workers. Factors independently associated with HIV infection in the multivariate analysis, regardless of sex work types, were injecting drug use, high self-perceived HIV risk, and age ≥ 25 years. Additional factors independently associated with HIV risk within each FSW subpopulation included having ever been married among street-based sex workers and inconsistent condom use with clients and having sex partners who injected drugs among venue-based sex workers. Apart from strategies addressing modifiable risk behaviours among all FSWs, targeted strategies to address specific risk behaviours within each FSW subpopulation should be adopted.
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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 | 0.000 |
| 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".