Impact of respiratory syncytial virus immunization in older adults: the importance of a valid burden estimation
Bibliographic record
Abstract
ABSTRACT Introduction In the province of Québec, Canada, a respiratory syncytial virus (RSV) immunization program restricted to seniors residing in long-term care facilities (LTCF) and those aged ≥75 years from private senior residences (PSR) was implemented in Fall 2024, with approximately 65% vaccine uptake in the targeted populations. Despite high vaccine effectiveness, the real-world impact of the RSV immunization program on population-level averted hospitalizations and the influence that RSV diagnostic test performance might have remains unknown. This study aimed to evaluate the impact of the first season (2024-25) of the intervention among older adults in Québec while accounting for laboratory test performance. Methods A prospective hospital-based surveillance (HospiVir) and health administrative databases were used to assess the intervention impact. Observed to expected approach and before/after ecological design using a difference-in-difference Poisson regression, both accounting for seasonal variations and trends in comparison groups, were used. Hospitalization incidence rate estimates based on hospital-based surveillance were adjusted for the laboratory test performances using Lash equations. Results Based on HospiVir, a 49% (95% confidence interval (CI): -80– -5) decrease in RSV-associated hospitalizations was observed among adults aged ≥75 years residing in PSR. This decrease was 23% (95% CI: -38–66) in the overall population ≥75 years. A smaller decrease for the overall population ≥75 years was observed using health administrative data, but it did not reach statistical significance (10%; 95% CI: -7–23). The impact of the immunization program did not change following adjustment for diagnostic test performance, while the absolute burden of RSV-associated hospitalizations varied according to the proportion of RSV test positivity. Conclusions The 2024-25 RSV immunization program was associated with an almost 50% reduction in hospitalizations in residents of PSR aged ≥75 years. The magnitude of this reduction was roughly twofold lower when considering the overall population aged ≥75 years. Expanding the target population and strengthening vaccine promotion efforts to improve uptake are both essential to enhance the population-level impact of the RSV immunization program.
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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 | 0.020 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".