Abstract: China's core megacities, characterized by frequent population mobility, busy international transportation, and complex ecological environments, have become areas at high risk for the importation and transmission of mosquito-borne viral infectious disease, such as dengue fever and Chikungunya fever. The risk of local transmission caused by imported cases of mosquito-borne viral infectious disease significantly increased, posing a severe challenge to the public health emergency response system. The existing prevention and control system is still affected by unbanlanced resource allocation, imperfect surveillance and early warning, and inconsistent implementation, making it difficult to meet the requirements of precise prevention and control of mosquito-borne viral infectious disease in megacities. To effectively improve the comprehensive prevention and control of mosquito-borne viral infectious disease in core megacities, this study developed a key technical toolkit according to actual requirements of the disease prevention and control in megacities. Following the core principles of scientific systematization and data-driven approaches, the toolkit integrates seven functional modules for surveillance, risk assessment and early warning, intervention for imported and local transmission, special scenario response, healthcare facility intervention, basic information management, and intelligent support based on national infectious disease control guidelines and cutting-edge research findings. By embedding machine learning algorithm model, the system can achieves core objectives, including multi-source data analysis, hierarchical risk early warning, precise multi-scenario adaptation, and coordinated response o all modules toprovide technical support solutions for customs, disease control institutions, medical institutions and communities, as well as the general public.