This paper presents a digital twin system for the early detection, modeling, and treatment of Varroa destructor infestations in honeybee colonies. The system integrates real-time sensor data, image-based mite detection using Vision Transformers, epidemiological simulations, and automated hyperthermia interventions. To improve global relevance and field adaptability, the framework incorporates regional disease surveillance protocols and technical innovations from Asia, particularly China, where advanced polymerase chain reaction (PCR) diagnostics, AI-enhanced imaging, and online disease management are increasingly deployed in apiculture. Simulation results demonstrate that proactive treatment guided by the digital twin significantly improves colony survival while maintaining energy efficiency, with annual power usage compatible with solarpowered systems. The approach offers a scalable and adaptive solution for precision beekeeping across diverse geographic and operational contexts.