APA
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Lyu, L., Gill, M. S., Stott, G., Subedi, S., Dailey, C., Veytsel, G., … Bahl, J. (2025). Tracing SARS-CoV-2 clusters across local scales using genomic data. Proceedings of the National Academy of Sciences of the United States of America.
Chicago/Turabian
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Lyu, L., Mandev S. Gill, G. Stott, Sachin Subedi, C. Dailey, G. Veytsel, M. Alabady, et al. “Tracing SARS-CoV-2 Clusters across Local Scales Using Genomic Data.” Proceedings of the National Academy of Sciences of the United States of America (2025).
MLA
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Lyu, L., et al. “Tracing SARS-CoV-2 Clusters across Local Scales Using Genomic Data.” Proceedings of the National Academy of Sciences of the United States of America, 2025.
BibTeX Click to copy
@article{l2025a,
title = {Tracing SARS-CoV-2 clusters across local scales using genomic data},
year = {2025},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
author = {Lyu, L. and Gill, Mandev S. and Stott, G. and Subedi, Sachin and Dailey, C. and Veytsel, G. and Alabady, M. and Fujimoto, K. and Penn, Ryker and Brown, P. and Sealy, R. and Bahl, J.}
}
Significance Pathogen genome sequencing has become a critical tool for outbreak response, leading to a rapid increase in the amount of available sequence data. Here, we present an analytical workflow to trace imported SARS-CoV-2 clusters through communities using large-scale genome datasets. Our approach pinpoints when, where, and how many introductions occurred, while also tracking the circulation of resulting clusters. By incorporating metrics such as the Source Sink Score, Local Import Score, and Persistence Time, our analysis reveals transmission heterogeneity between subregions of the focal area. These insights are essential for monitoring viral introductions, guiding targeted control measures, and enhancing the ability of local responders to address the challenges of current epidemics and future pandemics.