Surveillance for outbreaks of respiratory tract infections in nursing homes.
Bibliographic record
Abstract
BACKGROUND: Outbreaks of respiratory tract infections are common in long-term care facilities for older people. The objective of our study was to determine both the frequency of such outbreaks and their clinical and epidemiological features. METHODS: Prospective surveillance for outbreaks of respiratory tract infections and a retrospective audit of surveillance records were conducted in 5 nursing homes in metropolitan Toronto over 3 years. The clinical manifestations of infected residents were identified and microbiological investigations for causal agents were conducted. RESULTS: Sixteen outbreaks, involving 480 of 1313 residents, were identified prospectively during 1 144 208 resident-days of surveillance, for an overall rate of 0.42 infections per 1000 resident-days. Another 30 outbreaks, involving 388 residents, were identified retrospectively. Outbreaks occurred year-round, with no seasonal pattern. Pathogens included influenza virus, parainfluenza virus, respiratory syncytial virus, Legionella sainthelensi and Chlamydia pneumoniae. Multiple pathogens were detected in 38% (6/16) of the prospectively identified outbreaks. Of the 480 residents in the prospectively identified outbreaks 398 (83%) had a cough, 194 (40%) had fever and 215 (45%) had coryza. Clinical findings were nonspecific and could not be used to distinguish between causal agents. Pneumonia developed in 72 (15%) of the 480 residents, and 58 (12%) required transfer to hospital. The case-fatality rate was 8% (37/480). INTERPRETATION: Our findings emphasize the importance of adequate surveillance for outbreaks of respiratory tract infections in nursing homes and of early diagnosis so that appropriate interventions can be promptly instituted.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".