Disparities in hepatitis C care across Canadian provincial prisons: Implications for hepatitis C micro-elimination
Bibliographic record
Abstract
Background: Delivery of hepatitis C virus (HCV) care to people in prison is essential to HCV elimination. We aimed to describe current HCV care practices across Canada's adult provincial prisons. Methods: One representative per provincial prison health care team (except Ontario) was invited to participate in a web-based survey from January to June 2020. The outcomes of interest were HCV screening and treatment, treatment restrictions, and harm reduction services. The government ministry responsible for health care was determined. Non-nominal data were aggregated by province and ministry; descriptive statistical analyses were used to report outcomes. Results: The survey was completed by 59/65 (91%) prisons. On-demand, risk-based, opt-in, and opt-out screening are offered by 19 (32%), 10 (17%), 18 (31%), and 9 (15%) prisons, respectively; 3 prisons offer no HCV screening. Liver fibrosis assessments are rare (8 prisons access transient elastography, and 15 use aspartate aminotransferase to platelet ratio or Fibrosis-4); 20 (34%) prisons lack linkage to care programs. Only 32 (54%) prisons have ever initiated HCV treatment on site. Incarceration length and a fibrosis staging of ≥F2 are the most common eligibility restrictions for treatment. Opioid agonist therapy is available in 83% of prisons; needle and syringe programs are not available anywhere. Systematic screening and greater access to treatment and harm reduction services are more common where the Ministry of Health is responsible. Conclusions: Tremendous variability exists in HCV screening and care practices across Canada's provincial prisons. To advance HCV care, adopting opt-out screening and removing eligibility restrictions may be important initial strategies.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".