Real-time, multi-pathogen wastewater genomic surveillance with Freyja 2

Area of Science:

• Public Health
• Genomic Surveillance
• Bioinformatics

Background:

• Traditional infectious disease surveillance is resource-intensive and prone to bias.
• Wastewater genomic surveillance offers population-scale pathogen monitoring, even in low-resource settings.
• Current tools lack flexibility across sequencing platforms and adaptability to diverse pathogens.

Purpose of the Study:

• To introduce Freyja 2, an integrated bioinformatics tool for real-time pathogen lineage inference from complex samples.
• To develop and validate new methods for estimating pathogen prevalence and growth dynamics.
• To extend surveillance capabilities to multiple pathogens and diverse sequencing approaches.

Main Methods:

• Development of Freyja 2, an integrated bioinformatics pipeline.
• Implementation of novel algorithms for lineage prevalence and growth rate estimation.
• Validation across various sequencing platforms and low genomic coverage scenarios.

Main Results:

• Freyja 2 provides robust real-time inference of pathogen dynamics.
• The tool demonstrates adaptability across common sequencing platforms and low-coverage data.
• Multi-pathogen surveillance was enabled, tracking COVID-19, mpox, and H5N1 influenza, revealing hidden diversity and co-circulation.

Conclusions:

• Freyja 2 significantly enhances wastewater genomic surveillance capabilities.
• The tool supports flexible, multi-pathogen monitoring for public health emergencies.
• Freyja 2 reveals previously unreported pathogen diversity and co-circulation patterns.