Trends in hepatitis C care in Canada's provincial and territorial prisons from 2020 to 2024
Bibliographic record
Abstract
Background: National hepatitis C virus (HCV) elimination efforts are contingent on the provision of care in prisons. This study aimed to assess HCV care practices in Canada's provincial/territorial prisons in 2024, comparing trends from 2020 to 2024. Methods: From June 14 to October 31, 2024, one representative per prison health care team (excluding Nunavut) completed a web-based survey. The outcomes of interest were HCV screening, access to direct-acting antivirals (DAAs), linkage to care following release, and access to opioid agonist therapies (OAT) and prison-based needle and syringe programs (PNSPs). Non-nominal data were aggregated by province, and descriptive statistical analyses were used to report outcomes. Results: The survey was completed by 88/94 (94%) prisons. In total, 85 prisons offered HCV screening. On-demand (15/85; 18%), risk-based (1/85; 1%), and opt-in (9/85; 11%) screening declined since 2020, while opt-out (15/85; 18%) and combination (45/85; 53%) screening increased. Reflex RNA testing occurred in over half (46/85; 54%) of prisons. DAAs were offered in 74/88 (84%) prisons, and 65/74 (88%) provided the remainder of DAAs at release to facilitate treatment completion. In 2024, the majority (78/88; 89%) of prisons facilitated continuity of care following release. OAT was available in most prisons (83/88; 94%), and in 2024, more prisons offered OAT for people who had never been on OAT (73/83; 88%). Not a single prison had implemented PNSPs. Conclusions: While there were improvements in prison-based HCV care from 2020 to 2024, HCV care was still not equivalent to that in the community in 2024, jeopardizing HCV elimination efforts both in prisons and in surrounding communities.
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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 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".