Hepatitis B Screening and Vaccination Strategies for Newly Arrived Adult Canadian Immigrants and Refugees: A
Bibliographic record
Abstract
Background: Immigrants have increased mortality from hepatocellular carcinoma as compared to the host populations, primarily due to undetected chronic hepatitis B virus (HBV) infection. Despite this, there are no systematic programs in most immigrant-receiving countries to screen for chronic HBV infection and immigrants are not routinely offered HBV vaccination outside of the universal childhood vaccination program. Methods and findings: A cost-effective analysis was performed to compare four HBV screening and vaccination strategies with no intervention in a hypothetical cohort of newly-arriving adult Canadian immigrants. The strategies considered were a) universal vaccination, b) screening for prior immunity and vaccination, c) chronic HBV screening and treatment, and d) combined screening for chronic HBV and prior immunity, treatment and vaccination. The analysis was performed from a societal perspective, using a Markov model. Seroprevalence estimates, annual transition probabilities, health-care costs (in Canadian dollars), and utilities were obtained from the published literature. Acute HBV infection, mortality from chronic HBV, quality-adjusted life years (QALYs), and costs were modeled over the lifetime of the cohort of immigrants. Costs and QALYs were discounted at a rate of 3 % per year. Screening for chronic HBV infection, and offering treatment if indicated, was found to be the most cost-effective intervention and was estimated to cost $40,880 per additional QALY gained, relative to no intervention. This strategy
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".