Impacts of the SARS-CoV-2 pandemic on the seasonal pattern of hospitalizations for acute respiratory diseases among children in Alberta, Canada
Bibliographic record
Abstract
Introduction: Acute infectious respiratory diseases (ARD) among children generally have a biennial pattern – peak incidence is highest every other winter. This seasonal pattern of ARD was interrupted in 2020 by SARS-CoV-2 and non-pharmaceutical interventions (NPI). We conducted a population based retrospective cohort study in Alberta, that measured the impact on (i) the weekly incidence of hospitalizations to quantify healthcare use, (ii) the weekly percent of PICU admissions to monitor clinical severity, and (iii) the weekly average age at discharge to characterise the affected population. Methods: From Apr 2003-Dec 2023, all hospital discharges and PICU admissions for ARD (i.e. bronchiolitis, pneumonia, influenza-like-illness, and croup) among children < 18 years old were identified in the provincial hospital Discharge Abstract Database. Weekly incidence of hospital discharge was calculated using population denominators. Weekly percent PICU admissions was calculated using all hospital discharges as the denominator. Weekly average age at discharge was calculated from birth to discharge in months. Seasonal autoregressive-integrated-moving-average (SARIMA) models predicted the expected weekly outcomes from Apr 2020 onward. Incidence ratios and percent change compared observed versus expected outcomes. Analyses were conducted in R version 4.2.2 (2022-10-31) and R studio build 2022.12.0+353. Results: There were 63,776 hospitalizations for ARD among children from Apr 2003-Dec 2023: 22,963 (36.01%) for bronchiolitis, 23,977 (37.44%) for pneumonia, 10,833 (16.97%) for influenza-like-illness, and 4,984 (7.81%) for croup. Of the hospitalizations, 4,167 (6.53%) included a PICU admission. The average weekly incidence of hospitalization for ARD per 100,000 children decreased 12.71-fold during Dec 2020-Feb 2021 (0.82 observed vs. 10.42 [95%CI 5.11, 15.73] expected) and increased 1.51-fold during Dec 2022-Feb 2023 (16.28 observed vs. 10.77 [95%CI 4.71, 16.83] expected). The average percentage of PICU admissions steadily increased from 4.07% (95%CI 1.22%, 6.91%) in Dec 2003-Feb 2004 to 10.48% (95%CI 8.36%, 12.60%) in Dec 2019-Feb 2020. There was no significant change in the percentage of PICU admissions in Dec 2020-Feb 2021 and Dec 2022-Feb 2023, 11.17% (95%CI 0.00%, 26.32%) and 11.86% (95%CI 9.33%, 14.39%) respectively. During each winter season, the average age at discharge decreased to 25 months (95%CI 17.85, 33.74) annually. Similar patterns for incidence of hospitalizations, percent PICU admissions, and average age at discharge were observed for bronchiolitis, pneumonia, influenza-like-illness, and croup. Discussion: SARS-CoV-2 and NPI had significant impacts on provincial hospitalization for ARD among children. Initially hospitalizations for ARD decreased 12.71-fold during Dec 2020-Feb 2021. With SARS-CoV-2 vaccine availability, increased population immunity, and relaxation of NPI, hospitalizations for ARD increased 1.51-fold during Dec 2022-Feb 2023. However, there was no change in clinical severity based on percent PICU admissions, and no change in affected population based on average age at discharge.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| 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) | 0.003 | 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".