Predictors of SARS-CoV-2 transmission in congregate living settings: a multicenter prospective study
Bibliographic record
Abstract
BACKGROUND: Older adults residing in congregate living settings (CLS) such as nursing homes and independent living facilities remain at increased risk of morbidity and mortality from coronavirus disease 2019. We performed a prospective multicenter study of consecutive severe acute respiratory coronavirus virus 2 (SARS-CoV-2) exposures to identify predictors of transmission in this setting. METHODS: Consecutive resident SARS-CoV-2 exposures across 17 CLS were prospectively characterized from 1 September 2022 to 1 March 2023, including factors related to environment, source, and exposed resident. Room size, humidity, and ventilation were measured in locations where exposures occurred. Predictors were incorporated in a generalized estimating equation model adjusting for the correlation within CLS. RESULTS: Among 670 consecutive exposures to SARS-CoV-2 across 17 CLS, transmission occurred among 328 (49.0%). Increased risk was associated with nursing homes (odds ratio (OR) = 90.8; 95% CI, 7.8-1047.4), Jack and Jill rooms (OR = 2.2; 95% CI, 1.3-3.6), from source who was pre-symptomatic (OR = 11.2; 95% CI, 4.1-30.9), symptomatic (OR = 6.5; 95% CI, 1.4-29.9), or rapid antigen test positive (OR = 35.6; 95% CI, 5.6-225.6), and in the presence of secondary exposure (OR = 6.3; 95% CI, 1.6-24.0). Exposure in dining room was associated with reduced risk (OR = 0.02; 95% CI, 0.005-0.08) as was medium room size (OR = 0.3; 95% CI, 0.2-0.6). Recent vaccination of exposed resident (OR = 0.5; 95% CI, 0.3-1.0) and increased ventilation of room (OR = 0.9; 95% CI, 0.8-1.0) were marginally associated with reduced risk. CONCLUSION: Prospective assessment of SARS-CoV-2 exposures in CLS suggests that source characteristics and location of exposure are most predictive of resident transmission. These findings can inform risk assessment and further opportunities to prevent transmission in CLS.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".