Estimating the respiratory syncytial virus-associated hospitalisation burden in older adults in European countries: a systematic analysis
Bibliographic record
Abstract
BACKGROUND: With respiratory syncytial virus vaccines recently approved for use among older adults, country-level respiratory syncytial virus (RSV) disease burden estimates are needed to inform local RSV immunisation strategy. We aimed to estimate country-level RSV hospitalisation burden in older adults in Europe. METHODS: We compiled data on RSV hospitalisation burden in adults aged ≥ 60 years in Europe from published studies (systematic review: PROSPERO CRD42024516945), surveillance data, and unpublished data from international collaborators. We adjusted for diagnostic testing, clinical specimens, and case definitions through statistical modelling techniques and generated country-level hospitalisation rate estimates; for countries with no available data, we developed an ensemble model to predict RSV hospitalisation rates. We also estimated RSV in-hospital case fatality ratio (hCFR) for countries with available data. RESULTS: We included 14 studies (3 unpublished studies). The adjusted RSV-associated hospitalisation rates were overall 2.2 to 6.4 times higher than unadjusted estimates. Among 5 countries with available data, adjusted annual RSV hospitalisation rates ranged from 193/100,000 person-years in the Netherlands (95% confidence interval [CI]: 125-304) and Finland (141-274) to 414/100,000 in Denmark (322-514). The RSV hospitalisation rates predicted by the ensemble model in 23 additional countries ranged from 223/100,000 to 317/100,000 person-years. RSV hCFR ranged from 6.73% (4.63-9.69) in Spain to 10.14% (4.91-19.79) in Switzerland. CONCLUSIONS: This study addresses knowledge gaps in RSV hospitalisation burden among older adults in Europe while highlighting the importance of adjusting for RSV case under-ascertainment. These findings might be relevant for country's considerations of RSV immunisation strategies for older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".