High HIV risk in a cohort of male sex workers from Nairobi, Kenya
Bibliographic record
Abstract
OBJECTIVES: Men who have sex with men (MSM) are at high risk of HIV-1 acquisition and transmission, yet there remains limited data in the African context, and for men who sell sex to men (MSM SW) in particular. METHODS: We enrolled 507 male sex workers in a Nairobi-based prospective cohort study during 2009-2012. All participants were offered HIV/STI screening, counselling and completed a baseline questionnaire. RESULTS: Baseline HIV prevalence was 40.0% (95% CI 35.8% to 44.3%). Prevalent HIV infection was associated with age, less postsecondary education, marijuana use, fewer female partners and lower rates of prior HIV testing. Most participants (73%) reported at least two of insertive anal, receptive anal and insertive vaginal sex in the past 3 months. Vaginal sex was reported by 37% of participants, and exclusive MSM status was associated with higher HIV rates. Condom use was infrequent, with approximately one-third reporting 100% condom use during anal sex. HIV incidence was 10.9 per 100 person-years (95% CI 7.4 to 15.6). Predictors of HIV risk included history of urethral discharge (aHR 0.29, 95% CI 0.08 to 0.98, p=0.046), condom use during receptive anal sex (aHR 0.05, 95% CI 0.01 to 0.41, p=0.006) and frequency of sex with male partners (aHR 1.33/sex act, 95% CI 1.01 to 1.75, p=0.04). CONCLUSIONS: HIV prevalence and incidence were extremely high in Nairobi MSM SW; a combination of interventions including increasing condom use, pre-exposure prophylaxis and access to effective treatment is urgently needed to decrease HIV transmission in this key population.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".