Estimating the Incidence of First RSV Hospitalization in Children Born in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Respiratory syncytial virus (RSV) contributes significantly to morbidity in children, placing substantial burdens on health systems, thus RSV vaccine development and program implementation are a public health priority. More data on burden are needed by policymakers to identify priority populations and formulate prevention strategies as vaccines are developed and licensed. METHODS: Using health administrative data, we calculated incidence rates of RSV hospitalization in a population-based birth cohort of all children born over a six-year period (May 2009 to June 2015) in Ontario, Canada. Children were followed until their first RSV hospitalization, death, 5th birthday, or the end of the study period (June 2016). RSV hospitalizations were identified using a validated algorithm based on International Classification of Diseases, 10th Revision, and/or laboratory-confirmed outcomes. We calculated hospitalization rates by various characteristics of interest, including calendar month, age groups, sex, comorbidities, and gestational age. RESULTS: The overall RSV hospitalization rate for children <5 years was 4.2 per 1000 person-years (PY) with a wide range across age groups (from 29.6 to 0.52 per 1000 PY in children aged 1 month and 36-59 months, respectively). Rates were higher in children born at a younger gestational age (23.2 per 1000 PY for those born at <28 weeks versus 3.9 per 1000 PY born at ≥37 weeks); this increased risk persisted as age increased. While the majority of children in our study had no comorbidities, rates were higher in children with comorbidities. For all age groups, rates were highest between December and March. CONCLUSIONS: Our results confirm the high burden of RSV hospitalization and highlight young infants are at additional risk, namely premature infants. These results can inform prevention efforts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".