Disease burden attributable to respiratory syncytial virus outbreaks in long-term care
Bibliographic record
Abstract
Background: Respiratory syncytial virus (RSV) disease burden is significant among children; however, RSV can also cause excess morbidity and mortality among older adults. Populations in long-term care homes (LTCHs) may be at greater risk of exposure and increased infection severity. The objectives of this article are to identify evidence regarding disease burden and outcome severity attributable to RSV outbreaks among residents and staff in LTCHs; and to highlight reported population and outbreak characteristics. Methods: All types of evidence were eligible for inclusion. Data utilized by included studies was between the end of the 2010 H1N1 influenza pandemic and the beginning of the coronavirus disease 2019 (COVID-19) pandemic. Evidence from the following countries was considered: G7, the European Union, Australia and New Zealand. A total of 167 articles were identified; 58 full texts were analyzed and four sources of evidence were eligible for inclusion. Data related to population characteristics, outbreak type and resident and staff outcomes were manually charted. Results: There is a paucity of evidence sources pertaining to RSV outbreak burden among residents and staff in LTCHs. Outbreak duration ranged from 13 to 21 days. For each outbreak, 4-7 residents had confirmed RSV infection. Attack rates ranged from 12% to 38%. A spectrum of disease attributable to RSV outbreaks in LTCHs was identified, ranging from mild cold-like symptoms to death. Conclusion: Integration of RSV into existing respiratory pathogen surveillance programs is important to characterize susceptibility, transmissibility and virulence of RSV in at-risk populations. There is a need for public health organizations to publish the findings from outbreak investigations to provide evidence to inform RSV outbreak prevention and response in LTCH settings.
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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 | 0.008 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".