This project investigates how avian influenza (bird flu) spreads and undergoes genetic changes and identifies the key factors driving these genetic changes and spread. It elicits the spatial and genetic patterns of avian influenza in birds, mammals, and humans, aiming to assess the pandemic potential of this virus, which has had a 50% mortality rate in people infected during the past 30 years. Understanding the risk of spillover to humans requires a comprehensive understanding of the influenza ecosystem, an interconnected network of factors involving humans, animals, and the environment. The findings are being organized into a database for public access to support translation of what is learned from the project to practice by informing and optimizing measures to mitigate both the economic impacts on the agricultural sector, a core sector of the bioeconomy, and the public health risks posed by emerging influenza variants. This study aims to understand the genetic evolution of avian influenza, particularly a highly pathogenic H5N1 virus lineage over time and identify the ecological factors that drive human infections and viral change. Central to the study is a systematic analysis and characterization of the spatiotemporal distributions of viral genotypes and their genetic divergence from precursor avian influenza viruses. It leverages advanced geospatial modeling, machine learning, and geospatial artificial intelligence (GeoAI) techniques to identify key viral traits, such