Outbreak of SARS-CoV-2 infection at a large refugee shelter in Toronto, April 2020: a clinical and epidemiologic descriptive analysis
Bibliographic record
Abstract
BACKGROUND: There is high risk of transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in congregate settings, including shelters. This study describes a coronavirus disease 2019 (COVID-19) outbreak and corresponding reported symptomatology at a shelter in Toronto. METHODS: This clinical and epidemiologic analysis focuses on a COVID-19 outbreak at a dedicated refugee shelter in downtown Toronto. All adult residents on site at the shelter were offered SARS-CoV-2 testing on Apr. 20, 2020. At the time of testing, residents were screened for 3 typical COVID-19 symptoms (fever, cough and shortness of breath). Among those who tested positive, a more comprehensive clinical assessment was conducted 1 day after testing and a standardized 15-item symptom screen was administered by telephone 14 days after testing. We report rates of positive test results and clinical symptoms with each assessment interval. RESULTS: = 5) reported fever, cough or shortness of breath at the time of testing. On more detailed assessment 1 day later, 70.8% (17/24) reported a broader range of symptoms. During the 14 days after testing, 87.5% (21/24) reported symptoms of infection. INTERPRETATION: We found a high rate of SARS-CoV-2 infection in this shelter population. Our study underscores the high risk of SARS-CoV-2 transmission in congregate living settings and the importance of mobilizing timely testing and management of symptomatic, paucisymptomatic and asymptomatic residents in shelters.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".