Enhanced Surveillance of Acute Hepatitis B and C in Four Health Regions in Canada, 1998 TO 1999
Bibliographic record
Abstract
OBJECTIVE: To assess the incidence and risk factors for acute hepatitis B and acute hepatitis C in a defined Canadian population. PATIENTS AND METHODS: An enhanced surveillance system was established in October 1998 to identify cases of acute hepatitis B and C infections in four regions in Canada, with a total population of approximately 3.2 million people. Information on demographic and clinical characteristics, laboratory results and potential risk factors was collected using predefined questionnaires. RESULTS: A total of 79 cases of acute hepatitis B and 102 cases of acute hepatitis C were identified from October 1998 to December 1999, resulting in an incidence rate of 2.3 and 2.9/100,000 person-years, respectively. Males had higher incidence rates than females. The incidence of acute hepatitis B peaked at age 30 to 39 years for both males and females, whereas acute hepatitis C peaked at 30 to 39 years for males and 15 to 29 years for females. At least 34% of acute hepatitis B and 63% of acute hepatitis C were associated with injection drug use. Persons who were 15 to 39 years of age were more likely to report injection drug use as a risk factor. Heterosexual contact was reported to be a risk factor for 36.6% of acute hepatitis B cases and 3.5% of acute hepatitis C cases. CONCLUSIONS: The surveillance provides national incidence estimates of clinically recognized acute hepatitis B and C. Both hepatitis B and C are important public health threats to Canadians. Prevention efforts for both diseases should focus on injection drug use, especially for people aged 15 to 39 years. Risky sexual behaviour is also a major concern in prevention of hepatitis B in Canada.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| 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".