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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".