The Prevalence of Hepatitis A in Children in British Columbia
Bibliographic record
Abstract
BACKGROUND: The risk of hepatitis A virus (HAV) infection during childhood is difficult to estimate without population serosurveys because HAV-related symptoms are often mild at this age. Few serosurveys have been conducted in Canada. The present study surveyed teenagers in two nonurban regions of British Columbia where the historical rate of reported HAV either exceeded (region A) or was less than (region B) the historical provincial rate. METHODS: A point prevalence survey of salivary HAV-specific immunoglobulin G was conducted in high schools among grade 9 students in regions A and B. A questionnaire was used to gather sociodemographic data. The survey was extended to grade 1 and grade 5 students in community 1 of region B. Associations between risk factors and prior infection were evaluated by logistic regression. RESULTS: Eight hundred eleven grade 9 students were tested. Antibody to HAV was detected in 4.7% of students in region A (95% CI 2.9% to 7.2%) and 9.6% of students in region B (95% CI 6.9% to 12.9%). The region B figure reflected HAV antibody prevalence rates of 19.5% in community 1 and 2.5% in the remainder of the region. Younger students in community 1 had low HAV antibody to HAV prevalence rates (3.9% for grade 1 and 3.1% for grade 5), and positive tests in this community were associated with a particular school, foreign travel and brief residence. The risk factors for HAV infection in grade 9 students were not determined. CONCLUSIONS: Children in nonurban areas of British Columbia are generally at low risk of HAV infection during the first decade of life regardless of the reported population rates, thereby permitting the consideration of school-based HAV immunization programs.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".