Hepatitis C (HCV) prevalence in citizens of the Métis Nation of Ontario
Bibliographic record
Abstract
BACKGROUND: Hepatitis C virus (HCV) infection is a major global concern, with Indigenous Peoples bearing the highest burden. Previous studies exploring HCV prevalence within Indigenous populations have predominantly used a pan-Indigenous approach, consequently resulting in limited availability of Métis-specific HCV data. The Métis are one of the three recognized groups of Indigenous Peoples in Canada with a distinct history and language. The Métis Nation of Ontario (MNO) is the only recognized Métis government in Ontario. This study aims to examine the prevalence of self-reported HCV testing and positive results among citizens of the MNO, as well as to explore the association between sociodemographic variables and HCV testing and positive results. METHODS: A population-based online survey was implemented by the MNO using their citizenship registry between May 6 and June 13, 2022. The survey included questions about hepatitis C testing and results, socio-demographics, and other health related outcomes. Census sampling was used, and 3,206 MNO citizens responded to the hepatitis C-related questions. Descriptive statistics and bivariate analysis were used to analyze the survey data. RESULTS: Among the respondents, 827 (25.8%, CI: 24.3-27.3) reported having undergone HCV testing and 58 indicated testing positive, resulting in a prevalence of 1.8% (CI: 1.3-2.3). Respondents with a strong sense of community belonging, higher education levels, and lower household income were more likely to report having undergone HCV testing. Among those who had undergone testing, older age groups, individuals with lower education levels, and retired individuals were more likely to test positive for HCV. CONCLUSION: This study is the first Métis-led and Métis-specific study to report on HCV prevalence among Métis citizens. This research contributes to the knowledge base for Métis health and will support the MNO's health promotion program and resources for HCV. Future research will examine the actual HCV incidence and prevalence among MNO citizens.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".