Investigation of a severe SARS-CoV-2 outbreak in a long-term care home early in the pandemic
Bibliographic record
Abstract
BACKGROUND: The implementation of outbreak management measures has decreased the frequency and severity of SARS-CoV-2 outbreaks in Ontario long-term care homes. We describe the epidemiological and laboratory data from one of the first such outbreaks in Ontario to assess factors associated with its severity, and the impact of progressive interventions for infection control over the course of the outbreak. METHODS: We obtained line list and outbreak data from the public health unit to describe resident and staff cases, severity and distribution of cases over time and within the outbreak facility. Where available, we obtained data on laboratory specimens from the Public Health Ontario Laboratory and performed whole genome sequencing and phylogenetic analysis of viral specimens from the outbreak. RESULTS: Among 65 residents of the long-term care home, 61 (94%) contracted SARS-CoV-2, with a case fatality rate of 45% (28/61). Among 67 initial staff, 34 (51%) contracted the virus and none died. When the outbreak was declared, 12 staff, 2 visitors and 9 residents had symptoms. Resident cases were located in 3 of 4 areas of the home. Phylogenetic analysis showed tight clustering of cases, with only 1 additional strain of genetically distinct SARS-CoV-2 identified from a staff case in the third week of the outbreak. No cases were identified among 26 new staff brought into the home after full outbreak measures were implemented. INTERPRETATION: Rapid and undetected viral spread in a long-term care home led to high rates of infection among residents and staff. Progressive implementation of outbreak measures after the peak of cases prevented subsequent staff cases and are now part of long-term care outbreak policy in Ontario.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".