Estimation de la prévalence de l'hépatite B et C chez les immigrants au Canada
Bibliographic record
Abstract
Background: Hepatitis B virus (HBV) and hepatitis C virus (HCV) infections are sexually transmitted and blood-borne infections that Canada is committed to eliminate as public health concerns. Accurate epidemiological estimates require cross-sectional data as input. The objective of this study was to estimate the prevalence of present HBV infection (hepatitis B surface antigen-positive) and proportion aware of their infection, the vaccine-induced HBV immunity, the prevalence of HCV antibodies (anti-HCV-positive), the prevalence of present HCV infection (RNA-positive) and proportion aware of their infection, in the household population in Canada. These outcomes were also examined by selected demographic characteristics. Methods: A total of 7,543 sera from participants of the Canadian Health Measure Survey (CHMS) cycles 5 (2016-2017) and 6 (2018-2019) who consented to participate in Statistics Canada's Biobank were tested to determine their HBV and HCV status. Information from the CHMS household questionnaire was linked to the laboratory results to report on sociodemographic characteristics and awareness of infection. Results: The stored serum combined response rate for this study, which takes into account households' and respondents' participation in the CHMS and the Biobank was 42.8%. The estimated prevalence of present HBV infection among people aged 14 to 79 years was 0.4% (95% CI: 0.1%-0.7%), of whom 49.0% (95% CI: 15.4%-82.6%) were aware of their infection. An estimated 39.0% (95% CI: 37.0%-41.0%) of people aged 11 to 79 years had laboratory evidence of vaccine-induced HBV immunity. An estimated 0.5% (95% CI: 0.2%-0.8%) of people aged 14 to 79 years were positive for anti-HCV, and 0.2% (95% CI: 0.0%-0.3%) had a present infection (RNA-positive), of whom 51.2% (95% CI: 9.5%-92.9%) were aware of their infection. Conclusion: Cross-sectional data using nationally representative surveys are essential in assessing the burden of viral hepatitis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".