Toward elimination of hepatitis A and B in Europe: vaccination successes, challenges, and opportunities
Bibliographic record
Abstract
INTRODUCTION: Hepatitis B and hepatitis A are vaccine-preventable infections of global concern. Hepatitis B virus (HBV) and hepatitis A virus (HAV) vaccines available in Europe are underutilized in some age groups. While most European countries implemented childhood HBV universal routine vaccination (URV), vaccination coverage among adults remains low. Low HAV vaccination coverage among high-risk populations due to variable national vaccination policies, low awareness of vaccination benefits, and other barriers, increases the risk for outbreaks. AREAS COVERED: We discuss the awareness of hepatitis B and hepatitis A burden in different populations in Europe, vaccination recommendations, successes, challenges, and opportunities for their implementation. EXPERT OPINION: Awareness of at-risk populations and HBV/HAV vaccination recommendations should be raised among healthcare providers and the general population to increase access to vaccination. Increasing awareness that HBV vaccination contributes to reduction in the incidence of hepatocellular carcinoma can motivate adults to get vaccinated. Adult HBV URV may be considered in Europe, as in the United States, pending cost-effectiveness assessment at national levels. HAV vaccination recommendations should be updated and expanded to all at-risk persons. National HBV/HAV targets and vaccination strategies should be actively promoted to accelerate the elimination of viral hepatitis in Europe.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".