Fine-scale patterns of SARS-CoV-2 spread from identical pathogen sequences
Pathogen genomics can provide insights into underlying infectious disease transmission patterns<sup>1,2</sup>, but new methods are needed to handle modern large-scale pathogen genome datasets and realize this full potential<sup>3-5</sup>. In particular, genetically proximal viruses should be highly informative about transmission events as genetic proximity indicates epidemiological linkage. Here we use pairs of identical sequences to characterize fine-scale transmission patterns using 114,298 SARS-CoV-2 genomes collected through Washington State (USA) genomic sentinel surveillance with associated age and residence location information between March 2021 and December 2022. This corresponds to 59,660 sequences with another identical sequence in the dataset. We find that the location of pairs of identical sequences is highly consistent with expectations from mobility and social contact data. Outliers in the relationship between genetic and mobility data can be explained by SARS-CoV-2 transmission between postcodes with male prisons, consistent with transmission between prison facilities. We find that transmission patterns between age groups vary across spatial scales. Finally, we use the timing of sequence collection to understand the age groups driving transmission. Overall, this study improves our ability to use large pathogen genome datasets to understand the determinants of infectious disease spread.
Authors
- Lauren Frisbie (ORCID: https://orcid.org/0000-0002-4267-8448)
- Erica Ryke (ORCID: https://orcid.org/0000-0002-4056-1465)
- JohnAric M. Peterson
- Miguel I. Paredes (ORCID: https://orcid.org/0000-0002-9712-1663)
- Trevor Bedford (ORCID: https://orcid.org/0000-0002-4039-5794)
- Andrew Delgado (ORCID: https://orcid.org/0000-0001-5675-4096)
- Hong Xie (ORCID: https://orcid.org/0000-0001-6610-0723)
- Luis Fernando Gamboa (ORCID: https://orcid.org/0000-0002-7273-7381)
- Philip Dykema (ORCID: https://orcid.org/0000-0002-2158-3175)
- Pavitra Roychoudhury (ORCID: https://orcid.org/0000-0002-4567-8232)
- Chris Frazar
- Amanda C. Perofsky (ORCID: https://orcid.org/0000-0001-7341-9193)
- Allison Black (ORCID: https://orcid.org/0000-0002-6618-4127)
- Holly Halstead
- Jeremy Stone (ORCID: https://orcid.org/0000-0002-7565-2463)
- Alexander L. Greninger (ORCID: https://orcid.org/0000-0002-7443-0527)
- David Reinhart (ORCID: https://orcid.org/0009-0009-1975-4180)
- Lea M. Starita (ORCID: https://orcid.org/0000-0003-2870-5099)
- Cécile Viboud (ORCID: https://orcid.org/0000-0003-3243-4711)
- Kevin Kong
- Cécile Tran Kiem (ORCID: https://orcid.org/0000-0003-0563-8428)
- Drew MacKellar
- Amelia Weixler
- Allison Thibodeau
- Cory Yun
- F Aragona
Institutions
- Washington State Department of Health (US)
- National Institutes of Health (US)
- Cape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa (ZA)
- Howard Hughes Medical Institute (US)
- University of Washington (US)
- Fred Hutch Cancer Center (US)
- Brotman Baty Institute (US)
- Fogarty International Center (US)
Publication Details
- Journal
- Nature
- Published
- 2025-03-05
- DOI
- https://doi.org/10.1038/s41586-025-08637-4
- Citations
- 12
- Primary Topic
- COVID-19 epidemiological studies
- Type
- article
- Field-Weighted Citation Impact
- 16.42