The Changing Landscape of Respiratory Viruses Contributing to Hospitalizations in Quebec, Canada: Results From an Active Hospital-Based Surveillance Study
Bibliographic record
Abstract
BACKGROUND: A comprehensive description of the combined effect of SARS-CoV-2 and respiratory viruses other than SARS-CoV-2 (ORVs) on acute respiratory infection (ARI) hospitalizations is lacking. OBJECTIVE: This study aimed to compare the viral etiology of ARI hospitalizations before the pandemic (8 prepandemic influenza seasons, 2012-13 to 2019-20) and during 3 pandemic years (periods of increased SARS-CoV-2 and ORV circulation in 2020-21, 2021-22, and 2022-23) from an active hospital-based surveillance network in Quebec, Canada. METHODS: We compared the detection of ORVs and SARS-CoV-2 during 3 pandemic years to that in 8 prepandemic influenza seasons among patients hospitalized with ARI who were tested systematically by the same multiplex polymerase chain reaction (PCR) assay during periods of intense respiratory virus (RV) circulation. The proportions of infections between prepandemic and pandemic years were compared by using appropriate statistical tests. RESULTS: During prepandemic influenza seasons, overall RV detection was 92.7% (1384/1493) (respiratory syncytial virus [RSV]: 721/1493, 48.3%; coinfections: 456/1493, 30.5%) in children (<18 years) and 62.8% (2723/4339) (influenza: 1742/4339, 40.1%; coinfections: 264/4339, 6.1%) in adults. Overall RV detection in children was lower during pandemic years but increased from 58.6% (17/29) in 2020-21 (all ORVs; coinfections: 7/29, 24.1%) to 90.3% (308/341) in 2021-22 (ORVs: 278/341, 82%; SARS-CoV-2: 30/341, 8.8%; coinfections: 110/341, 32.3%) and 88.9% (361/406) in 2022-23 (ORVs: 339/406, 84%; SARS-CoV-2: 22/406, 5.4%; coinfections: 128/406, 31.5%). In adults, overall RV detection was also lower during pandemic years but increased from 43.7% (333/762) in 2020-21 (ORVs: 26/762, 3.4%; SARS-CoV-2: 307/762, 40.3%; coinfections: 7/762, 0.9%) to 57.8% (731/1265) in 2021-22 (ORVs: 179/1265, 14.2%; SARS-CoV-2: 552/1265, 43.6%; coinfections: 42/1265, 3.3%) and 50.1% (746/1488) in 2022-23 (ORVs: 409/1488, 27.5%; SARS-CoV-2: 337/1488, 22.6%; coinfections: 36/1488, 2.4%). No influenza or RSV was detected in 2020-21; however, their detection increased in the 2 subsequent years but did not reach prepandemic levels. Compared to the prepandemic period, the peaks of RSV hospitalization shifted in 2021-22 (16 weeks earlier) and 2022-23 (15 weeks earlier). Moreover, the peaks of influenza hospitalization shifted in 2021-22 (17 weeks later) and 2022-23 (4 weeks earlier). Age distribution was different compared to the prepandemic period, especially during the first pandemic year. CONCLUSIONS: Significant shifts in viral etiology, seasonality, and age distribution of ARI hospitalizations occurred during the 3 pandemic years. Changes in age distribution observed in our study may reflect modifications in the landscape of circulating RVs and their contribution to ARI hospitalizations. During the pandemic period, SARS-CoV-2 had a low contribution to pediatric ARI hospitalizations, while it was the main contributor to adult ARI hospitalizations during the first 2 seasons and dropped below ORVs during the third pandemic season. Evolving RVs epidemiology underscores the need for increased scrutiny of ARI hospitalization etiology to inform tailored public health recommendations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".