4.10-P9The effectiveness of Hepatitis B/C testing and linkage-to-care for migrant populations: a mixed methods systematic review
Bibliographic record
Abstract
Background: Every year over 350,000 deaths have been attributed to hepatitis infection, a significant proportionate of which are migrants. Migration dynamics changes transmission patterns and increases disease burden. Comprehensive understanding of current hepatitis testing and linkage-to-care interventions for migrants is needed. This study aims to synthesise aggregative evidence on the effectiveness, barriers, and experiences of hepatitis testing and linkage-to-care for migrants to alleviate the global burden of hepatitis. Methods: A mixed-method systematic review with thematic analysis approach was conducted to synthesise qualitative, quantitative, and aggregative evidence. Meta-analysis was conducted to measure the effect of screening and linkage-to-care across various settings and migrant populations. Qualitative studies were contextualised to generate thematic frameworks of barriers and facilitators built upon hepatitis B/C management cascade. Results: We searched five electronic databases and grey literature published between 2007-2017. Of the 1448 articles screened, 116 quantitative, 44 qualitative, and 10 mixed-method studies were eligible for data extraction. The pooled estimated yield of hepatitis B (HBV) virus screening was 54.86 HBsAg + (95% CI: 39.56–70.15; I2 = 97.80%; p < 0.0001) per 1,000 migrants. The yield of hepatitis C virus (HCV) screening was 24.95 anti-HCV + (95% CI: 16.79–33.11; I2 = 93.74%; p < 0.0001) per 1,000 migrants. Our conceptual framework indicated that community-based decentralised screening for migrants with active outreach programmes to cover population-specific barriers potentially diminish losses throughout testing and linkage-to-care cascade. A collaboration strategy should consist of the success of community partnerships, use of original language in recruiting and educational sessions, and culturally targeted patient navigators to provide extra assistance. Conclusion: Our study provides an estimate for the effectiveness of HBV and HCV testing and link-to-care interventions for migrant populations. Main message: Prioritisation of community-based decentralised Hepatitis B/C screening for migrants with population-specific outreach programmes and collaborating linkage-to-care processes can alleviate the global burden of hepatitis.
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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 | 0.032 | 0.129 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.014 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.002 |
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".