A32 POPULATION-BASED ESTIMATE OF HEPATITIS C VIRUS PREVALENCE IN ONTARIO, CANADA
Bibliographic record
Abstract
Hepatitis C virus (HCV) is the most burdensome infectious illness in Canada. Current screening strategies miss a significant proportion of cases, leaving many undiagnosed. Elevated HCV prevalence in the baby-boomer cohort has prompted calls for birth-cohort screening in this group. However, Canada lacks population-level data to support this recommendation. The aim of this study was to obtain a population-based estimate of the prevalence of HCV infection in Ontario residents born between 1945 and 1974, estimate of the number of HCV cases by age cohort in Canada, and generate evidence to underpin policy recommendations on birth-cohort screening. We tested anonymized residual sera in five-year age-sex bands, weighted according to the population across Ontario, for anti-HCV antibody, and tested all antibody positive and 10% of negative sera for HCV RNA. We performed descriptive epidemiological analysis and used a logistic regression model to determine HCV risk-factors. Of 10,006 sera analyzed, 155 (1.55%, confidence interval (CI) 1.31, 1.79) were positive for HCV antibody. For males, who comprised 107/155 (69.03%) of positive samples, the highest prevalence was 3.00% (95% CI 1.95, 4.39), for those born between 1960 – 1964. For females, the highest prevalence was 1.56% (95% CI 0.83, 2.65), for those born between 1955 – 1959. Both male sex and year-band of birth were significantly associated with positive HCV serostatus. Eighty of 145 (55.2%) antibody positive sera were also RNA positive, and 17/993 (1.7%) antibody negative sera were RNA positive. Using a previously published cost-effectiveness model, our analysis showed that a birth-cohort screening program for Ontario would be cost-effective. HCV prevalence in Ontario is highest among those in baby-boomer birth cohort, and higher than previous estimates. Given the development of highly effective, curative therapy, birth cohort screening should be strongly considered, particularly for those born between 1950 – 1969. Public Health Ontario Project Initiation Fund
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| 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".