Prevalence of sexually transmitted infections including HIV in street-connected adolescents in western Kenya
Bibliographic record
Abstract
PURPOSE: The objectives of this study were to characterise the sexual health of street-connected adolescents in Eldoret, Kenya, analyse gender disparity of risks, estimate the prevalence of sexually transmitted infections (STIs), and identify factors associated with STIs. METHODS: A cross-sectional study of street-connected adolescents ages 12-21 years was conducted in Eldoret, Kenya. Participants were interviewed and screened for Chlamydia trachomatis, Neisseria gonorrhoeae, Trichomonas vaginalis, herpes simplex virus-2, syphilis and HIV. Descriptive statistics and logistic regression were used to identify factors associated with having any STI. RESULTS: Of the 200 participants, 81 (41%) were female. 70.4% of females and 60.5% of males reported sexual activity. Of those that participated in at least one STI test, 28% (55/194) had ≥1 positive test, including 56% of females; 14% (28/194) had >1 positive test. Twelve females and zero males (6% overall, 14.8% of females) were HIV positive. Among females, those with HIV infection more frequently reported transactional sex (66.7% vs. 26.1%, p=0.01), drug use (91.7% vs. 56.5%, p=0.02), and reported a prior STI (50.0% vs. 14.7%, p<0.01). Having an adult caregiver was less likely among those with HIV infection (33.3% vs. 71.0%, p=0.04). Transactional sex (AOR 3.02, 95% CI (1.05 to 8.73)), a previous STI (AOR 3.46 95% CI (1.05 to 11.46)) and ≥2 sexual partners (AOR 5.62 95% (1.67 to 18.87)) were associated with having any STI. CONCLUSIONS: Street-connected adolescents in Eldoret, Kenya are engaged in high-risk sexual behaviours and females in particular have a substantial burden of STIs and HIV. There is a need for STI interventions targeted to street-connected youth.
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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 | 0.001 | 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) | 0.002 | 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".