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Leveraging mobility data to analyze persistent SARS-CoV-2 mutations and inform targeted genomic surveillance
Riccardo Spott1, Mathias W Pletz1,2, Carolin Fleischmann-Struzek1,2
1Institute for Infectious Diseases and Infection Control, Jena University Hospital, Jena, Germany.
Elife
|January 15, 2025
Summary
Combining mobile service data with genomic surveillance enhances tracking of SARS-CoV-2 variants like Alpha (B.1.1.7). This approach improves pandemic surveillance efficiency and identifies potential sampling biases for targeted responses.
Area of Science:
- Epidemiology
- Genomic Surveillance
- Public Health
Background:
- The rapid global spread of SARS-CoV-2 necessitates advanced surveillance methods.
- Tracking viral lineage transmission is challenging due to cross-country movement.
- Integrated genomic surveillance combining diverse data sources is crucial for pandemic management.
Purpose of the Study:
- To investigate the utility of mobile service data combined with genomic and metadata for SARS-CoV-2 surveillance.
- To assess the spread of SARS-CoV-2 Alpha (B.1.1.7) variants in Thuringia, Germany.
- To evaluate the potential of mobility data in guiding and improving genomic surveillance strategies.
Main Methods:
- Sequencing of over 6500 SARS-CoV-2 Alpha genomes with associated patient isolation dates and postal codes.
- Integration of a large dataset of publicly available German Alpha genomes and Thuringia mobile service data.
- Phylogenetic analysis to identify distinct mutation variants and their spread patterns.
Main Results:
- Identification of nine persistent SARS-CoV-2 Alpha variants, with seven forming distinct phylogenetic clusters.
- Mobile service data correlated with variant spread, revealing potential sampling biases for low-prevalence variants.
- Successful proof-of-concept for a mobility-guided sampling strategy during Omicron (B.1.1.7) sublineage BQ.1.1 surveillance.
Conclusions:
- Combining mobile service data with SARS-CoV-2 genomic surveillance offers a powerful tool for targeted and responsive pandemic monitoring.
- Mobility data can retrospectively assess surveillance effectiveness and prospectively guide sampling efforts.
- This integrated approach enhances the ability to track and respond to emerging viral variants.
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