HIV testing and its associated factors among street-based female sex workers in Iran: results of a national rapid assessment and response survey
Bibliographic record
Abstract
BACKGROUND: Female sex workers (FSWs) are at a disproportionate risk of sexually transmitted infections and they may face significant barriers to HIV testing. This study aimed to examine HIV testing prevalence and its associated factors among street-based FSWs in Iran. METHOD: A total of 898 FSWs were recruited from 414 venues across 19 major cities in Iran between October 2016 and March 2017. Eligible FSWs were women aged 18 years of age who had at least one commercial sexual intercourse in the previous year. HIV testing was defined as having tested for HIV in the lifetime. Bivariable and multivariable logistic regression were used to examine the correlates of HIV testing. We report adjusted odds ratios (aOR) and their 95% confidence intervals (CI). RESULT: Overall, 57.8% (95%CI: 20.0, 88.0) of participants reported having tested for HIV, and HIV prevalence among FSWs who tested for HIV was 10.3% (95%CI: 7.5, 13.0). The multivariable model showed that unstable housing (aOR: 8.86, 95%CI: 2.68, 29.32) and drug use (aOR: 3.47, 95%CI: 1.33, 9.06) were associated with increased likelihood of HIV testing. However, FSWs with a higher level of income were less likely to be tested for HIV (aOR: 0.09, 95%CI: 0.02, 0.43). CONCLUSION: Almost one in ten street-based FSWs had never tested for HIV. These findings suggest the need for evidence-based strategies such as outreach support and HIV self-testing to improve HIV testing in this marginalized population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".