Prevalence and contribution of respiratory viruses in the community to rates of emergency department visits and hospitalizations with respiratory tract infections, chronic obstructive pulmonary disease and asthma
Bibliographic record
Abstract
BACKGROUND: The individual and combined contribution of viral prevalence in the community to Emergency Department (ED) visits and hospitalizations with respiratory tract infections (RTIs), chronic obstructive pulmonary disease (COPD) and asthma is unclear. METHODS: A retrospective analysis on daily viral positive tests and daily ED visits and hospitalizations between 01/01/2003 to 31/12/2013 in Ontario, Canada. Viral data was collected from the Centre for Immunization and Respiratory Infectious Diseases (CIRID). The Canadian Institute for Health Information reports daily ED visits and hospitalizations for RTIs, COPD and asthma as a primary diagnosis. RESULTS: There were 4,365,578 ED visits with RTIs of which 321,719 (7.4%) were admitted to hospital; 817,141 ED visits for COPD of which 260,665 (31.9%) were admitted and 649,666 ED visits with asthma of which 68,626 (10.6%) were admitted. The percentage of positive tests to influenza A and B, respiratory syncytial virus (RSV), parainfluenza and adenovirus prevalence explained 57.4% of ED visits and 63.8% of hospitalizations for RTI, 41.4% of ED visits and 39.2% of hospitalizations with COPD but only 1.5% of ED visits and 2.7% of hospitalizations for asthma. The further addition of human metapneumovirus, rhinovirus and coronavirus over the final 3 years accounted for 66.7% of ED visits and 74.4% of hospitalizations for RTI, 52.5% of visits and 48.2% of hospitalizations for COPD, and only 13.3% of visits and 10.4% of hospitalizations for asthma. CONCLUSIONS: Community respiratory viral epidemics are major drivers of ED visits and hospitalizations with RTIs and COPD but only a modest contributor to asthma.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".