HGT-BioGuard: A Global Heterogeneous Graph Transformer for Early-Warning Biosurveillance

HGT-BioGuard represents a paradigm shift in pandemic preparedness through an AI-driven biosurveillance system that fuses heterogeneous global data streams—international flight patterns and SARS-CoV-2 genomic mutations—into a unified Heterogeneous Graph Transformer (HGT) model. By modeling complex relationships between airports, viral lineages, and their spatiotemporal evolution, BioGraph enables real-time prediction of emerging COVID-19 hotspots and probabilistic origin tracing of novel variants. Our system demonstrates that cross-domain data integration at scale provides the critical early warning capability that was missing during the COVID-19 pandemic. HGT-BioGuard doesn't just detect outbreaks; it anticipates them, buying public health officials the single most valuable resource in pandemic response: time. The model's heterogeneous architecture naturally accommodates multi-scale data—from local variant detection to global mobility patterns—creating a dynamic threat assessment framework that adapts as the virus evolves. Built on open datasets including OpenSky Network flight data and GISAID/Nextstrain genomic sequences, BioGraph showcases how defensive AI technology can transform reactive public health response into proactive biological defense. This isn't just another surveillance tool—it's a concrete implementation of how integrated data systems can create meaningful early warning capabilities against emerging biological threats.