Defining the Burden of Disease of RSV in Europe: estimates of RSV-associated hospitalisations in children under 5 years of age. A systematic review and modelling study
Bibliographic record
Abstract
Abstract Background Respiratory syncytial virus (RSV) infections cause an estimated 22-50 million episodes of acute lower respiratory infections (ALRI) every year in children younger than 5 years. To date, no overall estimate of RSV-associated hospitalisations in children under 5 years has been published for the European Union (EU). Through statistical modelling, we estimated the RSV hospitalisation burden in children under 5 years of age in EU countries and Norway, by age group and country. Methods We collated national RSV-associated hospitalisation estimates calculated using linear regression models in children under 5 years via the RESCEU project for Denmark, England, Finland, Norway, the Netherlands and Scotland during 2006-2018. A systematic literature review was conducted to collect additional estimates. Using the multiple imputation and nearest neighbour matching extrapolation methods, we estimated RSV-associated hospitalisation rates in all EU countries. Results Additional estimates for Spain and France were found in the literature and added to the analysis. We estimated that an average of 245,244 (95%CI 224,688-265,799) hospital admissions with a respiratory infection per year were associated with RSV in children under the age of 5, with most cases occurring among children aged less than 1 year (75%). Infants aged less than 2 months represented the most affected group (71.6 per 1,000 children; 95%CI: 66.6-76.6). The hospitalisation rates varied widely across countries: for example, estimated rates in the 0-2 months age group ranged from 47.4 (37.5-57.3) per 1,000 in the Netherlands to 98.3 (88.5-108.1) per 1,000 in France. Conclusion To our knowledge, this is the first attempt to estimate the overall RSV hospitalisation burden in children under the age of 5 years in the EU. Our findings will help support decisions regarding prevention efforts, and they will also represent an important benchmark to understand changes in the RSV burden following the introduction of RSV immunisation programs 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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.021 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".