Burden of disease of RSV in infants, children and pregnant women and people
Bibliographic record
Abstract
Background: Passive immunization products for infants and pregnant women and people have sparked interest in understanding Canada's respiratory syncytial virus (RSV) burden. This rapid review examines RSV burden of disease in infants, young children and pregnant women and people. Methods: Electronic databases were searched to identify studies and systematic reviews reporting data on outpatient visits, hospitalizations, intensive care unit admissions, deaths and preterm labour associated with RSV. We also contacted Canadian respiratory virus surveillance experts for additional data. Results: Overall, 17 studies on infants and young children and 10 studies on pregnant women and people were included, in addition to primary surveillance data from one Canadian territory (Yukon). There were higher rates of medical utilization for infants than older children. Hospitalization rates were highest in infants under six months (more than 1% annually), with 5% needing intensive care unit admission, but mortality was low. Severe outcomes often occurred in healthy full-term infants and burden was higher than influenza. Respiratory syncytial virus attack rate was 10%-13% among pregnant women and people. Only one study found a higher hospitalization rate in pregnant women and people compared to non-pregnant women and people. Limited evidence was found on intensive care unit admission, death and preterm birth for pregnant women and people. Conclusion: While risk of severe outcomes is larger in high-risk infants and children, healthcare burden is greatest in healthy term infants. The RSV severity for pregnant women and people appears to be similar to that for non-pregnant women and people.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".