Evidence map›Paper›PMID 40773234›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Tracing SARS-CoV-2 clusters across local scales using genomic data.

Leke Lyu, Mandev Gill, Guppy Stott, Sachin Subedi, Cody Dailey, Gabriella Veytsel, Magdy Alabady, Kayo Fujimoto, Ryker Penn, Pamela Brown and 2 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

12 authors.

Leke LyuInstitute of Bioinformatics, University of Georgia, Athens, GA 30602.ORCID 0009-0004-5657-8271
Mandev GillInstitute of Bioinformatics, University of Georgia, Athens, GA 30602.ORCID 0000-0001-7818-1081
Guppy StottInstitute of Bioinformatics, University of Georgia, Athens, GA 30602.
Sachin SubediInstitute of Bioinformatics, University of Georgia, Athens, GA 30602.ORCID 0000-0002-1145-8880
Cody DaileyInstitute of Bioinformatics, University of Georgia, Athens, GA 30602.
Gabriella VeytselInstitute of Bioinformatics, University of Georgia, Athens, GA 30602.
Magdy AlabadyDepartment of Plant Biology, University of Georgia, Athens, GA 30602.
Kayo FujimotoDepartment of Health Promotion and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX 77030.ORCID 0000-0002-8445-2711
Ryker PennHouston Health Department, Houston, TX 77054.
Pamela BrownHouston Health Department, Houston, TX 77054.
Roger SealyHouston Health Department, Houston, TX 77054.
Justin BahlInstitute of Bioinformatics, University of Georgia, Athens, GA 30602.ORCID 0000-0001-7572-4300

Funding

NIAID Centers of Excellence for Influenza Research and Response: Universal Influenza Vaccine Research Activities75N93021C00018 · NIAID · UNIVERSITY OF GEORGIA · PI TOMPKINS, S. MARK · 2021 to 2025
$21.6M
HHS | Centers for Disease Control and Prevention (CDC) 75D30121C10133HHS | Centers for Disease Control and Prevention (CDC) NU50CK000626NIAID NIH HHS 75N93021C00018
6 · The paper itself

Abstract

A quantitative understanding of local transmission dynamics is essential for designing effective prevention strategies. In this study, we developed a computational workflow to identify viral introductions and trace locally circulating clusters. We analyzed over 26,000 SARS-CoV-2 genomes and their associated metadata, collected between January and October 2021, to explore introduction and local dispersal patterns in Greater Houston, a major metropolitan area known for its demographic diversity. Our analysis identified more than 1,000 independent introduction events, resulting in clusters of varying sizes. The majority of introductions originated from domestic sources, while international introductions occurred earlier and were associated with larger cluster sizes. An analysis of locally circulating clusters revealed age-structured transmission dynamics. Geographic reconstruction of cluster spread identified Harris County as the primary viral source for surrounding areas. The outbreak in the source population was characterized by 1) a smaller proportion of new cases associated with external viral imports and 2) longer persistence times of circulating lineages. Overall, our high-resolution spatiotemporal reconstruction of the epidemic provides essential insights into the local-scale transmission landscape, supporting outbreak-specific, regional response strategies and public health planning.

Indexed as

COVID-19Genome, ViralSARS-CoV-2Cluster AnalysisDisease OutbreaksGenomicsHumansTexasgenomic epidemiologypandemic controlviral evolution

Identifiers

PMID40773234
PMCPMC12358902

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.