COVID-19 outbreak in a long-term care facility in Kelowna, British Columbia after rollout of COVID-19 vaccine in March 2021
Bibliographic record
Abstract
BACKGROUND: In March 2021, a coronavirus disease 2019 (COVID-19) outbreak was declared at a large long-term care and short stay facility in British Columbia, Canada-well after introduction of the vaccination program in long-term care facilities that resulted in a dramatic decline in the number of outbreaks in this type of setting. The objective of this study is to provide the descriptive epidemiology of this outbreak, in the context of partial immunization of both residents and staff at the facility. METHODS: The cases' information was extracted from a provincial information system (Panorama). Descriptive analysis was performed using Microsoft Excel and SAS. Outbreak management controls included, but were not limited to, asymptomatic testing and efforts to increase vaccination. RESULTS: Twenty-six cases among the 241 resident and three cases among the 418 staff (corresponding to attack rates of 10% and less than 1%, respectively) were identified. The attack rate in residents was considerably lower than the average attack rate for COVID-19 outbreaks in long-term care facilities before the vaccine rollout. Seventeen resident cases were either partially or fully immunized. Four of the eight hospitalized cases and two of the three deceased cases were partially immunized. Seventeen cases were temporary stay residents. The three staff cases were not vaccinated. Ten cases were identified as part of asymptomatic testing. CONCLUSION: Introduction of vaccination at facilities contributed to lower attack rates and higher numbers of asymptomatic cases in this outbreak. Screening asymptomatic individuals identified additional cases among vaccinated residents. Findings underscore the importance of achieving high vaccine coverage, including among temporary stay residents, to prevent virus introduction and subsequent unrecognized transmission opportunities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".