SARS-CoV-2 burden on the floor was associated with COVID-19 cases and outbreaks in two acute care hospitals: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Recent work demonstrated that detection of SARS-CoV-2 on the floor of long-term care facilities is associated with impending COVID-19 outbreaks. It is unknown if similar results will be observed in hospitals. METHODS: Floor swabs were prospectively collected weekly from healthcare worker-only areas (eg, staff locker rooms) at two hospitals in Ontario, Canada for 39 weeks. Floor swabs were processed for SARS-CoV-2 using quantitative reverse-transcriptase polymerase chain reaction. Results were reported as percentage of positive floor swabs and viral copy number. Grouped fivefold cross-validation was used to evaluate model outbreak discrimination. RESULTS: SARS-CoV-2 RNA was detected on 537 of 760 floor swabs (71%). At Hospital A, overall positivity was 90% (95% CI: 85%-93%; N = 280); at Hospital B, overall positivity was 60% (95% CI: 55%-64%; N = 480). There were four COVID-19 outbreaks at Hospital A and seven at Hospital B during the study period. The outbreaks consisted of primarily patient cases (ie, 140 patient cases and 4 staff cases). For every 10-fold increase in viral copies, there was a 22-fold higher odds of a COVID-19 outbreak (OR = 22.0, 95% CI 7.3, 91.8). The cross-validated area under the receiver operating curve for SARS-CoV-2 viral copies for predicting a contemporaneous outbreak was 0.86 (95% CI 0.82-0.90). CONCLUSION: Viral burden of SARS-CoV-2 on floors, even in healthcare worker-only areas, was strongly associated with COVID-19 outbreaks in those hospital wards. Built environment sampling may support hospital COVID-19 outbreak identification, fill gaps in traditional surveillance, and guide infection prevention and control measures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".