The algorithmic cartography of influenza's genomic plasticity: Integrated genomics, high-throughput sequencing and actionable public health surveillance

Background: Influenza viruses, with their segmented RNA genomes, exhibit remarkable genomic plasticity through antigenic drift and shift, enabling rapid evolution and persistent zoonotic threats. Traditional surveillance methods lack the resolution to monitor viral quasispecies and emerging zoonotic threats effectively.

Aim/Objectives: This comprehensive review synthesizes advancements in integrated phylogenomics and phylodynamics with computational methods for influenza surveillance that enhance the resolution, speed, and utility of influenza surveillance for public health action. 

Materials and Methods: We evaluated the comparative strengths of short-read (Illumina) and long-read (Oxford Nanopore) sequencing platforms for Whole-Genome Sequencing (WGS) of influenza. We also assessed bioinformatics pipelines from raw data quality control to sophisticated algorithmic analysis including variant calling (GATK, LoFreq), reassortment mapping (RDP4, GiRaF), and computational tracking of antiviral resistance markers.

Results: Integrated genomic and phylogenetic analysis provides high-resolution characterization of viral diversity, enabling precise identification of emerging clades and adaptive mutations. NGS platforms offer distinct advantages: Illumina provides exceptional accuracy for population-level surveillance, while Oxford Nanopore enables real-time sequencing for outbreak response and long-read capability for resolving reassortment events. Advanced computational tools successfully decode viral quasispecies, track antigenic drift and shift, and identify antiviral resistance markers, transforming raw sequence data into actionable insights.

Conclusions: The integrated framework transforms sequence data into actionable public health intelligence, enabling real-time evolutionary monitoring and predictive modeling essential for effective public health preparedness.

Implication of the Study: This multi-layered surveillance paradigm guides the transition toward One Health surveillance, integrating human, animal, and environmental data for comprehensive global health security.