Hospitalizations for all-cause pediatric acute respiratory diseases in Alberta, Canada, before, during, and after the COVID-19 pandemic: a population-level retrospective cohort study from 2010 to 2024
Bibliographic record
Abstract
Background: This population-level retrospective cohort study measured seasonal patterns of pediatric hospitalizations, pediatric intensive care unit (PICU) admissions, and average age of children diagnosed with acute respiratory diseases (ARD) during pre-pandemic, COVID-19 pandemic, and late/post-pandemic periods. Methods: From September 2010 through August 2024, all hospitalizations for ARD among children <18 years old were identified from the provincial Discharge Abstract Database, in Alberta, Canada. Seasonal autoregressive integrated moving average (SARIMA) models were developed based on pre-pandemic trends and predicted expected weekly outcomes with 95% confidence intervals (95% CI) from March 2020 onward. Observed and expected outcomes with 95% CI were compared to measure impacts during peak seasons. Findings: There were 52,839 ARD hospitalizations: 16,003 (30.29%) bronchiolitis, 7958 (15.06%) influenza-like illness, 14,366 (27.19%) pneumonia, 2989 (5.66%) croup, 10,266 (19.43%) asthma exacerbation, and 1257 (2.38%) COVID-19. Further, 4433 (8.39%) hospitalizations included a PICU admission. During the pre-pandemic period, hospitalizations for ARD had a biennial pattern, where the peak incidence was highest every other winter season. During the pandemic and late/post-pandemic periods, the average weekly incidence of hospitalization for ARD/100,000 children decreased 91.25% during winter 2020-2021 (1.03 observed vs. 11.81 [95% CI 7.30, 16.33] expected), increased 47.98% during winter 2022-2023 (18.06 observed vs. 12.20 [95% CI 7.06, 17.34] expected), and returned near pre-pandemic incidence during winter 2023-2024 (12.87 observed vs. 11.87 [95% CI 6.08, 17.67] expected) compared with incidence predicted by the SARIMA model. During winter 2022-2023 when hospitalizations surged, there was no significant change in the average weekly incidence of PICU admissions for ARD/100,000 children (2.07 observed vs. 1.26 [95% CI 0.26, 2.27] expected), nor percent PICU admissions (10.21% observed vs. 10.11% [95% CI 5.50, 14.73] expected), nor in average age (31.95 months observed vs. 34.20 months [95% CI 25.89, 42.52] expected). Interpretation: Hospitalizations for pediatric ARD decreased dramatically during winter 2020-2021, surged during winter 2022-2023, and returned near pre-pandemic incidence during winter 2023-2024. There was no lasting change in PICU admissions nor average age. Ongoing surveillance will describe the evolving seasonal pattern of ARD during the post-pandemic period. Funding: None.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".