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Record W4407551403 · doi:10.1016/j.lana.2025.101024

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

2025· article· en· W4407551403 on OpenAlexafffundabout
Christine D. Lukac, Brett Simms, Grace P. S. Kwong, Jessalyn K. Holodinsky, David W. Johnson, James D. Kellner

Bibliographic record

VenueThe Lancet Regional Health - Americas · 2025
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsAlberta Children's HospitalHotchkiss Brain InstituteAlberta Health ServicesAlberta HealthUniversity of Calgary
FundersPfizer CanadaAlberta Children's Hospital Research InstituteYork UniversitySimon Fraser UniversityGovernment of Alberta
KeywordsPandemicMedicineCoronavirus disease 2019 (COVID-19)Retrospective cohort studyCohortSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakPediatricsRespiratory systemCohort studyPopulationEmergency medicineVirologyEnvironmental healthInternal medicineOutbreakDiseaseInfectious disease (medical specialty)

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.092
GPT teacher head0.432
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2025
Admission routes3
Has abstractyes

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