Epidemiology of Hepatitis C over 28 years of monitoring Canadian blood donors: Insight into a low-risk undiagnosed population
Bibliographic record
Abstract
BACKGROUND: Hepatitis C is a blood-borne infection with the hepatitis C virus (HCV) that can progress to cirrhosis and liver cancer. About 70% (50-80%) of infections become chronic and exhibit anti-HCV and HCV nucleic acid (NAT) positivity. Direct acting oral pan genotypic antiviral treatment became available in 2014 and was free for most Canadians in 2018. Clinical screening for HCV infection is risk-based. About 1% of Canadians have been infected with HCV, with 0.5% chronically infected (about 25% unaware) disproportionately impacting marginalized groups. Blood donors are in good health, are deferred for risks such as injection drug use and can provide insight into the low-risk undiagnosed population. Here we describe HCV epidemiology in first-time blood donors over 28 years of monitoring. METHODS: All first-time blood donors in all Canadian provinces except Quebec (1993 to 2021) were analyzed. All blood donations were tested for HCV antibodies (anti-HCV) and since late 1999 also HCV NAT. A case-control study was also included. All HCV positive donors (cases) since 2005 and HCV negative donors (1:4 ratio controls) matched for age, sex and location were invited to complete a risk factor interview. Separate logistic regression models for anti-HCV positivity and chronic HCV assessed the association between age cohort, sex, region and neighbourhood material deprivation and ethnocultural concentration. CASE: control data were analysed by logistic regression. RESULTS: There were 2,334,238 donors from 1993 to 2021 included. Prevalence for anti-HCV was 0.33% (0.30,0.37) in 1993 and 0.07% (0.05,0.09) in 2021 (p < 0.0001). In 2021 0.03% (0.01,0.04) had chronic HCV. Predictors for both anti-HCV positivity and chronic HCV were similar, for chronic HCV were male sex (OR 1.8, 1.6,2.1), birth between 1945 and 1975 (OR 7.1, 5.9,8.5), living in the western provinces (OR 1.4, 1.2,1.7) and living in material deprived (OR 2.7, 2.1,3.5) and more ethnocultural concentrated neighbourhoods (OR 1.8, 1.3,2.5). There were 318 (35.4%) of chronic HCV positive and 1272 (39.6%) of controls who participated in case control interviews. The strongest risks for acquisition were injection drug use (OR 96.9, 22.3,420.3) and birth in a high prevalence country (OR 24.5, 11.2,53.6). CONCLUSIONS: Blood donors have 16 times lower HCV prevalence then the general population. Donors largely mirror population trends and highlight the ongoing prevalence of untreated infections in groups without obvious risks for acquisition missed by risk-based patient screening.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".