Inferring viral variants and fitness advantages from longitudinal wastewater sequencing data

During the SARS-CoV-2 pandemic, wastewater-based epidemiology emerged as an effective tool for monitoring infection dynamics. However, wastewater represents a pooled sample of incomplete viral genomic fragments originating from multiple individuals in the catchment area of a wastewater treatment plant, preventing the assembly of complete viral genomes. Existing computational pipelines are therefore limited in detecting new variants that are absent from clinical sequencing data. We developed FitNMF, an integrated viral dynamics and non-negative matrix factorization model that leverages the temp

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