Survival Sex Work Involvement as a Primary Risk Factor for Hepatitis C Virus Acquisition in Drug-Using Youths in a Canadian Setting
Bibliographic record
Abstract
OBJECTIVE: To examine whether there were differential rates of hepatitis C virus (HCV) incidence in injecting drug-using youths who did and did not report involvement in survival sex work. DESIGN: Data were derived from 2 prospective cohort studies of injecting drug users (May 1, 1996, to July 31, 2007). Analyses were restricted to HCV antibody-negative youths who completed baseline and at least 1 follow-up assessment. SETTING: Vancouver, British Columbia, Canada. PARTICIPANTS: Of 3074 injecting drug users, 364 (11.8%) were youths (aged 14-24 years) with a median age of 21.3 years and a duration of injecting drug use of 3 years. Main Exposure Survival sex work involvement. MAIN OUTCOME MEASURE: The Kaplan-Meier method and Cox proportional hazards regression were used to compare HCV incidence among youths who did and did not report survival sex work. RESULTS: Baseline HCV prevalence was 51%, with youths involved in survival sex work significantly more likely to be HCV antibody positive (60% vs 44%; P = .002). In baseline HCV antibody-negative youths, the cumulative HCV incidence at 36 months was significantly higher in those involved in survival sex work (68.4% vs 38.8%; P < .001). The HCV incidence density was 36.8 (95% confidence interval [CI], 24.2-53.5) per 100 person-years in youths reporting survival sex work involvement at baseline compared with 14.1 (9.4-20.3) per 100 person-years in youths not reporting survival sex work. In multivariate Cox proportional hazards analyses, survival sex work was the strongest predictor of elevated HCV incidence (adjusted relative hazard, 2.30; 95% CI, 1.27-4.15). CONCLUSION: This study calls attention to the critical need for evidence-based social and structural HCV prevention efforts that target youths engaged in survival sex work.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".