Continuing HIV Transmission Among Injection Drug Users in Eastern Central Canada: The SurvUDI Study, 1995 to 2000
Bibliographic record
Abstract
OBJECTIVE: To document HIV prevalence/incidence trends from 1995-2000 and associated risk factors among injection drug users (IDUs) in Eastern Central Canada as an indication of harm reduction strategy effectiveness. METHODS: Nonnominal cross-sectional data (one-time participants) and longitudinal data (repeat participants) were collected using convenience sampling. Participants provided informed consent for face-to-face interviews focused on injection drug use and sexual practices during the previous 6 months; oral fluid samples were taken for HIV testing by enzyme immunoassay. Unique encrypted codes for initially HIV-negative repeat participants permitted incidence rate calculations. RESULTS: In all, 6387 IDUs (median age, 31 years; range, 13-67; males, 73.5%) participated on 9724 occasions. HIV prevalence ranged from 4.7% (95% confidence interval [CI], 2.9-6.5) in semiurban areas to 20.1% (95% CI, 17.6-22.7) in Ottawa, Ontario. HIV incidence was 6.0 (95%CI, 4.5-7.6) per 100 person-years (py) in Montréal, Québec, 3.2 (95% CI, 2.2-4.2) per 100 py in Québec City and 7.0 (95% CI, 4.1-9.8) per 100 py in Ottawa/Hull. Reusing other IDUs' needles was reported by 38.4%. In multivariate logistic regression, IDUs injecting for 6 or more years were more likely to be HIV positive, particularly if cocaine was the predominant drug injected. Multivariate Cox regression revealed higher HIV incidence among those who predominantly injected cocaine, reused others' needles, had injected 6 years or more, injected with strangers, or were men reporting commercial sex work. CONCLUSIONS: These results reveal a volatile situation of continuing HIV transmission among IDUs in Eastern Central Canada.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".