Drivers and barriers of seasonal influenza vaccination in the European Union and European Economic area (EU/EEA): a systematic review
Bibliographic record
Abstract
Background Vaccination against seasonal influenza reduces disease burden in target groups such as older people, individuals with chronic diseases, pregnant women, small children and health care workers (HCWs). Vaccination policies and programmes vary and coverage is below the 75% EU Council Recommendation target in all EU/EEA member states except The Netherlands. A systematic review of the evidence about drivers and barriers to seasonal influenza vaccination uptake was conducted to inform national and EU level policies. Methods We searched Medline, EMBASE and the Cochrane Library for papers published in English between 2008 and 2012. Two authors screened articles, appraised quality and extracted data. A percentage of all articles were independently assessed with level of agreement evaluated and differences resolved by discussion. Results 29 of 4,981 articles met the inclusion criteria; among these were systematic reviews, randomized controlled trials (RCTs), cohort, case-control and cross sectional studies. For older people, standard reminder postcards or letters and personalized postcards or phone calls work. For individuals with chronic medical conditions, effectiveness varies by condition. Reminder systems do increase influenza vaccination rates in asthmatic children from 10% to a maximum of 21%. Among HCWs, there is strong evidence that multi-component campaigns - inclusion of education/promotion and improved access to vaccines - increase vaccination (up to 68.5%) in non-hospital settings. Mandatory vaccination policies achieve the highest uptake with vaccination rates over 95% consistently reported. Evidence on drivers and barriers of seasonal influenza vaccination for healthy children and pregnant women is limited to qualitative studies and natural experiments. Conclusions There is a shortage of peer-reviewed literature on the drivers and barriers to seasonal influenza vaccination. This systematic review identified strategies to improve uptake of seasonal influenza vaccination in target groups, particularly older people and HCWs. Successful interventions should be implemented to reduce the burden of influenza and related morbidity and mortality in the EU/EEA. Future interventions should be clearly defined and rigorously evaluated. Key messages EU/EEA states should prioritise evidence-based plans to improve influenza vaccination uptake. Priority groups, interventions & targets tailored to low, medium & high uptake countries should be agreed.
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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".