Incidence of Respiratory Syncytial Virus-Associated Hospitalization Among Adults in Ontario, Canada, 2017–2019
Bibliographic record
Abstract
BACKGROUND: Respiratory syncytial virus (RSV) causes substantial morbidity and mortality among adults. Given recent RSV vaccine authorizations, data on groups at highest risk are needed to support vaccine program decision making. METHODS: We identified adults aged ≥ 18 years hospitalized with laboratory-confirmed RSV and hospitalizations with RSV-related diagnostic codes in Ontario, Canada (2017-2019). We calculated incidence of hospitalization with 95% confidence intervals (CIs) using Poisson regression stratified by demographic and clinical risk factors, and substratified by age. We reported secondary outcomes including the proportion of individuals with fatal outcomes. RESULTS: Over 2 respiratory virus seasons, we identified 3928 RSV-associated hospitalizations. Incidence increased steadily with age from 2.0 (95% CI, 1.8-2.3) per 100 000 for those aged 18-49 years to 43.7 (95% CI, 41.0-46.6) per 100 000 for those aged 70-79 years, with a sharp increase to 134.7 (95% CI, 128.6-141.1) per 100 000 for those aged ≥ 80 years. Incidence was higher for those with comorbidities, including chronic kidney disease (receiving dialysis) (494.7; 95% CI, 410.7-595.8) and transplant recipients (370.9; 95% CI, 318.0-432.6), as well as for those living in lower (22.4; 95% CI, 21.1-23.7) versus higher-income neighborhoods (11.8; 95% CI, 10.8-12.8). Among those hospitalized, 10.3% (n = 403) died within 30 days of admission, and 93.1% of deaths occurred in those aged ≥ 60 years. Of survivors, 44.6% of community-dwelling adults aged ≥ 60 years had functional decline requiring formal supports at discharge. DISCUSSION: We found a substantial burden of RSV among older adults, particularly among those with preexisting medical conditions and those of lower socioeconomic status. These results will inform equitable vaccine recommendations for adults.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".