Prevalence of HIV and hepatitis C virus infections among inmates of Quebec provincial prisons
Bibliographic record
Abstract
BACKGROUND: To determine the prevalence of HIV and hepatitis C virus (HCV) infections and examine risk factors for these infections among inmates in Quebec provincial prisons. METHODS: Anonymous cross-sectional data were collected from January to June 2003 for men (n = 1357) and women (n = 250) who agreed to participate in the study and who completed a self-administrated questionnaire and provided saliva samples. RESULTS: The prevalence of HIV infection was 2.3% among the male participants and 8.8% among the female participants. The corresponding prevalence of HCV infection was 16.6% and 29.2%, respectively. The most important risk factor was injection drug use. The prevalence of HIV infection was 7.2% among the male injection drug users and 0.5% among the male non-users. Among the women, the rate was 20.6% among the injection drug users, whereas none of the non-users was HIV positive. The prevalence of HCV infection was 53.3% among the male injection drug users and 2.6% among the male non-users; the corresponding values among the women were 63.6% and 3.5%. INTERPRETATION: HIV and HCV infections constitute an important public health problem in prison, where the prevalence is affected mainly by a high percentage of injection drug use among inmates.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".