Prevention and assessment of infectious diseases among children and adult migrants arriving to the European Union/European Economic Association: a protocol for a suite of systematic reviews for public health and health systems
Bibliographic record
Abstract
Introduction The European Centre for Disease Prevention and Control is developing evidence-based guidance for voluntary screening, treatment and vaccine prevention of infectious diseases for newly arriving migrants to the European Union/European Economic Area. The objective of this systematic review protocol is to guide the identification, appraisal and synthesis of the best available evidence on prevention and assessment of the following priority infectious diseases: tuberculosis, HIV, hepatitis B, hepatitis C, measles, mumps, rubella, diphtheria, tetanus, pertussis, poliomyelitis (polio), Haemophilus influenza disease, strongyloidiasis and schistosomiasis. Methods and analysis The search strategy will identify evidence from existing systematic reviews and then update the effectiveness and cost-effectiveness evidence using prospective trials, economic evaluations and/or recently published systematic reviews. Interdisciplinary teams have designed logic models to help define study inclusion and exclusion criteria, guiding the search strategy and identifying relevant outcomes. We will assess the certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Ethics and dissemination There are no ethical or safety issues. We anticipate disseminating the findings through open-access publications, conference abstracts and presentations. We plan to publish technical syntheses as GRADEpro evidence summaries and the systematic reviews as part of a special edition open-access publication on refugee health. We are following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Protocols reporting guideline. This protocol is registered in PROSPERO: CRD42016045798.
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 | 0.150 | 0.180 |
| Meta-epidemiology (narrow) | 0.008 | 0.007 |
| Meta-epidemiology (broad) | 0.019 | 0.024 |
| Bibliometrics | 0.018 | 0.024 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.061 | 0.015 |
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".