The role of prison-based interventions for hepatitis C virus (HCV) micro-elimination among people who inject drugs in Montréal, Canada
Bibliographic record
Abstract
Abstract Background In Canada, hepatitis C virus (HCV) transmission primarily occurs among people who inject drugs (PWID) and people with experience in the prison system bare a disproportionate HCV burden. These overlapping groups of individuals have been identified as a priority populations for HCV micro-elimination in Canada, a country currently not on track to achieve its elimination targets. Considering the missed opportunities to intervene in provincial prisons, this study aims to estimate the population-level impact of prison-based interventions and post-release risk reduction strategies on HCV transmission among PWID in high HCV-burdened Canadian city, Montréal. Methods A dynamic HCV transmission model among PWID was developed and calibrated to community and prison bio-behavioural surveys in Montréal. The, the relative impact of prison-based testing and treatment or post-release linkage to care, alone or in combination with risk reduction strategies, was estimated from 2018 to 2030, and compared to counterfactual status quo scenario. Results Testing and linkage to care interventions implemented over 2018-30 could lead to the greatest declines in prevalence (23%; 95% Credible interval(CrI):17–31%), incidence (20%; 95%CrI: 10–28%), and prevent the most new chronic infections (8%; 95%CrI: 4–11%). Testing and treatment in prison could decrease prevalence, incidence, and fraction of prevented new chronic infections. Combining test and linkage to care with risk reduction measures could further its epidemiological impact, preventing 10% (95%CrI: 5–16%) of new chronic infections. When implemented concomitantly with community-based treatment scale-up, both prison-based interventions had synergistic effects, averting a higher fraction of new chronic infections. Conclusion Offering HCV testing and post-release linkage to care in provincial prisons, where incarcerations are frequent and sentences short, could change the course of the HCV epidemic in Montréal. Integration of post-release risk reduction measures and community-based treatment scale-up could also increase the impact of these interventions.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".