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Record W4406924199 · doi:10.1093/ofid/ofae631.1387

P-1205. The Impact of the COVID-19 Pandemic on Hospitalizations Associated with Respiratory Syncytial Virus (RSV) Illness Among Children and Adolescents in Ontario, Canada

2025· article· en· W4406924199 on OpenAlexaffabout
Sazini Nzula, A Goyette, Deshayne B. Fell, Natalie Nightingale, Maria Esther Perez Trejo, Calum S. Neish, Ana Gabriela Grajales

Bibliographic record

VenueOpen Forum Infectious Diseases · 2025
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsPfizer (Canada)
Fundersnot available
KeywordsMedicineRespiratory illnessPandemicCoronavirus disease 2019 (COVID-19)Respiratory systemSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakVirologyPediatricsVirusOutbreakInternal medicineDisease

Abstract

fetched live from OpenAlex

Abstract Background COVID-19 pandemic measures may have lowered general immunity against respiratory syncytial virus (RSV). It is therefore important to characterize RSV epidemiology and its impact on healthcare resources as core pandemic prevention strategies have been lifted.Figure 1.Counts of RSV hospitalizations in Ontario children and adolescents aged ≤17 years across 2010 – 2023.*Exact counts for 2010 – 2011 and 2020 – 2021 were suppressed for privacy reasons. Methods Patients aged ≤ 17 years hospitalized with RSV between July 1, 2010 and March 31, 2023 were identified from provincial administrative data at ICES, which captures healthcare encounters within Ontario’s publicly funded healthcare system. Annual outcomes were reported from July 1st to June 30th of the following year.Figure 2.Proportion of RSV hospitalizations in Ontario children and adolescents aged ≤17 years by seasonality across 2010 – 2023.*Exact counts for 2010 – 2011 and 2020 – 2021 were suppressed for privacy reasons. Results Between 2010-2020, 1,356-2,060 annual RSV hospitalizations were recorded, with a decrease in 2020-21 season to < 6 cases, followed by an increase to 1,617 (2021-22) and 4,298 (2022-23), likely due to consequences of pandemic-related restrictions (Figure 1). Prior to 2020, only 2-6% of RSV hospitalizations occurred during the non-RSV season (May-October); this increased to 18% in 2021-22 and 20% in 2022-23 (Figure 2). In 2022-23, hospitalizations were observed to be ∼2-fold that of previous years’ (2010-2021) for those < 12 months, while those hospitalized at 12-< 24 months or 2-17 years old were ∼3-fold and ∼5-7-fold higher, respectively. Interestingly, 2021-22 and 2022-23 had shorter median length of stay (LOS) in the intensive care unit (ICU) even while the same period had the greatest ICU utilization (14-17%; overall study period: 12%). In 2022-23, 55% more children hospitalized at < 4 or 4-< 7 months old had an ICU stay compared to the overall study period while their LOS in ICU remained similar. The median hospitalization costs remained consistent throughout the study period at ∼CAD$5,000, with slightly higher costs observed for 2021-2023 (∼CAD$5,300). Therefore, the total annual cost of RSV hospitalizations more than doubled from ∼CAD$12-16 million during 2010-2022 to ∼CAD$38M in 2022-23 due to the rise in hospitalized cases (Figure 3).Figure 3.Total costs of RSV hospitalizations in Ontario children and adolescents aged ≤17 years across 2010 – 2023. There were only <6 RSV hospitalizations reported for 2020 – 2021 likely due to the COVD-19 restrictions. All costs were standardized to 2021 Canadian dollars. Conclusion The impact of pandemic measures on RSV hospitalizations were substantial, with most of the consequences observed in 2022-23. Study findings suggest that older children were more impacted by the recent changes in RSV trends, and it is still unclear when pre-pandemic patterns will resume. Disclosures Sazini Nzula, PhD, Pfizer Canada: Employee Alexandra Goyette, MSc, Pfizer: Employee|Pfizer: Stocks/Bonds (Private Company) Deshayne B. Fell, PhD, Pfizer Inc.: Employment|Pfizer Inc.: Stocks/Bonds (Private Company) Ana Gabriela Grajales, MD, Pfizer Canada ULC: I am currently an employee in Medical Affairs|Pfizer Canada ULC: Stocks/Bonds (Public Company)

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)0.000
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 score0.038
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.017
GPT teacher head0.326
Teacher spread0.308 · 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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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