SARS-CoV-2 outbreak in a Canadian suburban tertiary hospital necessitating full facility closure: a descriptive observational study
Bibliographic record
Abstract
BACKGROUND: SARS-CoV-2 can cause outbreaks in community- and hospital-based settings. The aim of this study was to provide a detailed epidemiologic account of a hospital-wide SARS-CoV-2 outbreak and provide a description of case evaluations, transmission networks and the interventions implemented to stem the outbreak. METHODS: We conducted a retrospective descriptive study of a hospital-wide SARS-CoV-2 outbreak at the Misericordia Community Hospital (Edmonton) from June 21 to Aug. 14, 2020. We reviewed hospital chart, public health and occupational health records to determine demographics, case type (community- or hospital-acquired), need for critical care and outcome for each case linked to the outbreak (patients, hospital staff, and community and patient visitors). We developed detailed transmission networks using epidemiologic data to determine what variables may have contributed to transmission. RESULTS: Fifty-eight cases of SARS-CoV-2 infection were linked to this hospital outbreak (31 patients, 25 staff members and 2 visitors; 66% female, age range 19-97 years). One patient required critical care, and 11 deaths were recorded (all among inpatients). Most cases were hospital-acquired (91%), and 28% were asymptomatic at the time of diagnosis. The outbreak was composed of 2 clusters driven by protective equipment breaches, premature removal of precautions, transmission in small staff quarters and infection of a staff member after exposure to a wandering patient with dementia and asymptomatic, undetected SARS-CoV-2 infection. INTERPRETATION: A detailed epidemiologic review of this hospital-wide outbreak shows that a SARS-CoV-2 outbreak can involve complex transmission chains and clusters. Multipronged bundled approaches, aggressive contact tracing, and patient and staff prevalence screening are important to help bring such outbreaks under control, along with ongoing vigilance in detecting delayed cases.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".