Declines in HIV prevalence in female sex workers accessing an HIV treatment and prevention programme in Nairobi, Kenya over a 10-year period
Bibliographic record
Abstract
OBJECTIVES: Empirical time trends in HIV prevalence in female sex workers (FSWs) are helpful to understand the evolving HIV epidemic, and to monitor the scale-up, coverage, and impact of ongoing HIV prevention and treatment programmes. DESIGN: Serial HIV prevalence study. METHODS: We analyzed time trends in HIV prevalence in FSWs accessing services at seven Sex Worker Outreach Programme (SWOP) clinics in Nairobi from 2008 to 2017 (N = 33 560). The Mantel--Haenszel test for trend and independent samples Kruskal--Wallis test were used to analyze categorical and continuous variables, respectively. Multivariable binomial regression was used to estimate prevalence ratios/year, adjusting for several covariates. RESULTS: HIV prevalence decreased over time in all age groups. This was particularly evident among FSWs less than 25 years of age; HIV was 17.5% in 2008-2009, decreasing to 12.2% in 2010-2011, 8.3% in 2012-2013, 7.3% in 2014-2015, and 4.8% in 2016-2017 (P < 0.0001). Over time, FSWs reported increased condom use, particularly with regular partners, more frequent prior HIV testing, and were less likely to report a history of vaginal discharge (P < 0.0001). In adjusted analyses compared with 2008, HIV prevalence decreased in 2011 (aPR 0.64; 95% CI: 0.46-0.90), 2012 (aPR 0.58; 95% CI: 0.41-0.81), 2013 (aPR 0.53; 95% CI: 0.38-0.73), 2014 (aPR 0.48; 95% CI: 0.34-0.67), 2015 (aPR 0.50; 95% CI: 0.35-0.70), 2016 (aPR 0.40; 95% CI: 0.28-0.57), and 2017 (aPR 0.33; 95% CI: 0.22-0.50). CONCLUSION: HIV prevalence has decreased among FSW accessing SWOP in Nairobi, Kenya. This decline is consistent with the scale-up of HIV prevention and treatment efforts, both in FSWs and in the general 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 | 0.000 | 0.000 |
| 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".