Evidence map›Paper›PMID 40886221›Full record

ArticleAging clinical and experimental research2025

Analyzing SARS-CoV-2 case numbers and clustering to predict a nursing home outbreak.

Yasin Abul, Kevin McConeghy, Frank DeVone, Christopher Halladay, Stefan Gravenstein, James Rudolph

Abstract read
In one paragraph

Article in Aging clinical and experimental research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yasin AbulCenter of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI, USA. yasin_abul@brown.edu.
Kevin McConeghyCenter of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI, USA.
Frank DeVoneCenter of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI, USA.
Christopher HalladayCenter of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI, USA.
Stefan GravensteinCenter of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI, USA.
James RudolphCenter of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic devastated nursing homes, highlighting the urgent need for effective outbreak control measures. This study analyzed twice-weekly PCR surveillance data from 134 Veteran Affairs Community Living Centers (December 2021-June 2022) to identify early predictors of SARS-CoV-2 outbreaks. Among 16,353 residents (mean age 74, 96% male, 68% white), we identified 1,868 infections and evaluated neighborhood ward-level case counts and their association with subsequent infections over two-week periods. Epidemic unit-days with no initial cases had an 87.49% likelihood of remaining case-free, while those with ≥ 4 initial cases demonstrated a 38.5% probability of developing ≥ 4 additional cases. These findings indicate that early case clusters strongly predict larger outbreaks, underscoring the importance of rapid detection and intervention. Study limitations include demographic homogeneity and reliance on frequent PCR testing, potentially limiting generalizability. This research provides a valuable framework for refining outbreak definitions and improving infection control strategies for respiratory virus outbreaks in nursing homes.

Indexed as

COVID-19Disease OutbreaksNursing HomesSARS-CoV-2AgedAged, 80 and overCluster AnalysisFemaleHumansMaleUnited StatesCOVID-19Nursing homesOlder adultsOutbreak definitionSARS-CoV-2

Identifiers

PMID40886221
PMCPMC12399729

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.