HIV risks associated with incarceration among injection drug users: implications for prison-based public health strategies
Bibliographic record
Abstract
BACKGROUND: Recent policy announcements in Canada and the United States may potentially affect the risk environment for HIV transmission among incarcerated injection drug users (IDU). We sought to evaluate the potential impact of incarceration on HIV risk behaviour among the IDU enrolled in a prospective cohort study. METHODS: We examined patterns of incarceration among 1247 IDU participants enrolled in a 6-year prospective cohort study in Vancouver, Canada, and tested for potential associations between HIV risk behaviour and incarceration. Correlates of incarceration were identified using generalized estimating equations (GEE). RESULTS: At baseline, factors significantly associated with incarceration included daily injection heroin and injection cocaine use and inconsistent condom use with casual sexual partners. In a GEE analysis, factors independently associated with incarceration included: used syringe borrowing (adjusted odds ratio [AOR] = 1.36; [95% CI: 1.16-1.60]), used syringe lending (AOR = 1.31; [95% CI: 1.12-1.55]) and inconsistent condom use with casual sexual partners (AOR = 1.16; [1.02-1.33]). All variables P < 0.05. CONCLUSION: In our study, incarceration was independently associated with HIV transmission and acquisition behaviours. These findings suggest that increased rates of incarceration of IDU may be associated with increased HIV transmission among this group.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".