Liver health events: an indigenous community-led model to enhance HCV screening and linkage to care
Bibliographic record
Abstract
Despite high prevalence of hepatitis C virus (HCV), linkage to care and treatment for Indigenous people is low. In an Indigenous community in Saskatchewan, Canada a retrospective review identified 200 individuals (∼12% prevalence) had HCV antibodies though majority lacked ribonucleic acid (RNA) testing, and few received treatment despite availability of an effective cure. Following Indigenous oral traditions, focus group discussions were held with key community members and leadership. Participants emphasized the need for a community-based screening and treatment programme. A team of community members, peers and healthcare professionals developed a streamlined screening pathway termed 'liver health event' (LHE) to reduce stigma, reach undiagnosed, re-engage previously diagnosed, and ensure rapid linkage to care/treatment. LHEs began December 2016. Statistics were tracked for each event. As of July 2019, there were 10 LHEs with 540 participants, 227 hepatitis C tests and 346 FibroScans completed. This represented 294 unique individuals, of which 64.3% were tested, and of those, 40.8% were Ab positive. Among those positive for antibodies, 41.7% had active hepatitis C infections, and among these, 90% were linked to care, and 14 new positive individuals were identified. Following the success of LHEs, these were adapted and implemented in 10 other communities in this region, resulting in 17 additional LHEs. This intervention is reaching the undiagnosed and linking clients to care through a low-barrier and de-stigmatizing approach. It has facilitated collaboration, knowledge exchange and mentorship between Indigenous communities, significantly impacting health outcomes of Indigenous people in this region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".