Abstract: With the rapid advancement of information technology and data science, infectious disease surveillance and early warning technologies have experienced unprecedented development and application opportunities. These technologies play a crucial role and provide strong data support and decision-making basis in effectively responding to and rapidly controlling emerging infectious disease outbreaks and epidemics by enabling timely detection of infections, real-time tracking of transmission dynamics, trend forecasting and other aspects. This study systematically reviews the application of multi- channel data in infectious disease prevention and control both domestically and internationally. It also delves into the application scenarios, advantages and disadvantages of the main early warning models, aiming to provide technical and model support for infectious disease surveillance and early warning efforts. The study seeks to advance infectious disease prevention and control towards a more information-driven, intelligent and precise direction.