Transmission Dynamics of Avian Influenza in Human Populations: Integrating Artificial Intelligence as a Critical Predictive Parameter

Abstract

Avian influenza remains a significant zoonotic threat due to its rapid viral evolution, sporadic spillover into human populations, and potential to trigger large-scale outbreaks. Traditional surveillance systems often detect emerging infections only after substantial transmission has occurred, highlighting the need for predictive analytical tools capable of early outbreak detection. In this study, we investigate the transmission dynamics of avian influenza in human populations by integrating artificial intelligence–based data analysis with mathematical epidemic modeling. Historical human case data reported by the World Health Organization and the Centers for Disease Control and Prevention from 2003 to 2024 were analyzed using AI-assisted smoothing, regression-based forecasting, and scenario-based simulations to identify long-term epidemiological patterns and potential future trajectories. To provide a theoretical foundation for these empirical observations, we formulate a SEIR-type compartmental model incorporating an artificial intelligence control parameter that represents enhanced surveillance and intervention capability. Using the next-generation matrix method, the basic reproduction number is derived and analytical results are established for the stability of the disease-free equilibrium. The analysis demonstrates that improvements in AI-supported surveillance reduce the effective transmission rate and consequently decrease the reproduction number, leading to epidemic suppression when a critical threshold is exceeded. Simulation results further illustrate how enhanced surveillance and early detection can significantly alter outbreak trajectories under various epidemiological scenarios. These findings highlight the potential of integrating artificial intelligence with mathematical epidemiology to strengthen early warning systems, improve outbreak preparedness, and support One Health strategies for the control of avian influenza