Prevalencia del VIH en niños, niñas y adolescentes en situación de calle y explotación sexual comercial: una revisión sistemática
Bibliographic record
Abstract
The aim of this review was to describe HIV prevalence in children and youth living on the street and subject to commercial sexual exploitation, and the studies' characteristics in terms of place, time, population, and sample design. This was a systematic review, not a meta-analysis, based on an article search in 10 electronic databases: Science Direct, MEDLINE, OVID, LILACS, Wiley InterScience, MD Consult, Springer Link, Embase, Web of Science, and Ebsco. A complementary search was also performed in the libraries of schools of public health and webpages of U.N. agencies, besides the reference lists from the selected articles. We selected observational studies focused on children and youth living on the street and subject to commercial sexual exploitation, ranging in age from 10 to 20 years, with the results for HIV prevalence rates. A total of 9,829 references were retrieved, of which 15 met the inclusion criteria and comprise this descriptive summary. Of these 15 articles, 12 were conducted in children and youth living on the street and three in children subject to commercial sexual exploitation. All 15 were cross-sectional studies. HIV prevalence in children and youth living on the street ranged from 0% in Dallas, USA and Cochabamba, Bolivia to 37.4% in St. Petersburg, Russia. In children and youth living subject to commercial sexual exploitation, prevalence ranged from 2% in Toronto, Canada to 20% in Kolkata, India. In conclusion, HIV infection is present in children and youth living on the street and subject to commercial sexual exploitation. Measures are needed for prevention, diagnosis, and treatment as a public health priority and an ethical responsibility on the part of governments and society.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".