HIV seroprevalence among participants at a Supervised Injection Facility in Vancouver, Canada: implications for prevention, care and treatment
Bibliographic record
Abstract
North America's first government sanctioned medically supervised injection facility (SIF) was opened during September 2003 in Vancouver, Canada. This was in response to a large open public drug scene, high rates of HIV and hepatitis C transmission, fatal drug overdoses, and poor health outcomes among the city's injection drug users. Between December 2003 and April 2005, a representative sample of 1,035 SIF participants were enrolled in a prospective cohort that required completing an interviewer-administered questionnaire and providing a blood sample for HIV testing. HIV infection was detected in 170/1007 (17%) participants and was associated with Aboriginal ethnicity (adjusted Odds Ratio [aOR], 2.70, 95% Confidence Interval [95% CI], 1.84–3.97), a history of borrowing used needles/syringes (aOR, 2.0, 95% CI, 1.37–2.93), previous incarceration (aOR, 1.87, 95% CI, 1.11–3.14), and daily injection cocaine use (aOR, 1.42, 95% CI, 1.00–2.03). The SIF has attracted a large number of marginalized injection drug users and presents an excellent opportunity to enhance HIV prevention through education, the provision of sterile injecting equipment, and a supervised environment to self-inject. In addition, the SIF is an important point of contact for HIV positive individuals who may not be participating in HIV care and treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| 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".