Viral hepatitis C cascade of care: A population‐level comparison of immigrant and long‐term residents
Bibliographic record
Abstract
BACKGROUND & AIMS: Viral hepatitis C represents a major global burden, particularly among immigrant-receiving countries such as Canada, where knowledge of disparities in hepatitis C virus among immigrant groups for micro-elimination efforts is lacking. We quantify the hepatitis C cascades of care among immigrants and long-term residents prior to the introduction of direct-acting antiviral medications. METHODS: Using laboratory and health administrative records, we described the hepatitis C virus cascades of care in terms of diagnosis, engagement with care, treatment initiation, and clearance in Ontario, Canada (1997-2014). We stratified the cascade by immigrant and long-term resident groups and identify drivers at each stage using multivariable Poisson regression. RESULTS: We included 940 245 individuals in the study with an estimated hepatitis C prevalence of 167 923 (1.4%) overall, 23 759 (0.7%) among all immigrants, and 6019 (1.1%) among immigrants from hepatitis C endemic countries. Overall there were 104 616 individuals with reactive antibody results, 73 861 tested for viral RNA, 52 388 with viral RNA detected, 50 805 genotyped, 13 159 on treatment and 3919 with evidence of viral clearance. Compared to long-term residents, immigrants showed increased nucleic-acid testing (aRR: 1.09 [95%CI: 1.08, 1.10]), treatment initiation (aRR: 1.46 [95%CI: 1.38, 1.54]), and higher clearance rates (aRR: 1.07 [95%CI: 1.03, 1.11]). CONCLUSIONS: Hepatitis C virus is more prevalent among long-term residents compared to immigrants overall, however, immigrants from endemic countries are an important subgroup to consider for future screening and linkage to care initiatives. These findings are prior to the introduction of newer medications and provide a population-based benchmark for follow-up studies and evaluation of treatment programs and surveillance activities.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".