Urban Public Health Event Early Warning and Prediction System Based on ID3 Algorithm of Decision Tree Model

With the rapid development of social economy, urban public health events occur frequently, seriously affecting the life and safety of citizens. The early warning and prediction system of public health events refers to taking effective measures to control possible public health problems within a certain range through monitoring, analysis and prediction. This paper studies the application of decision tree model ID3 algorithm in the early warning and prediction system of urban public health events, with the purpose of improving the early warning ability when and before the occurrence of public health events. This paper applies qualitative and quantitative methods to study urban public health events, and analyzes the occurrence of events and the performance of the early warning system through experimental and comparative methods. The experimental data shows that the more users, the longer the execution time of the system, but the overall system response time does not exceed 25ms, which can meet certain prevention needs. Through research on the urban public health event early warning and prediction system, it is found that the system has good performance and short response time, which can effectively identify potential crises, improve the feasibility and early warning effect of the system, and improve the defense ability of relevant departments to respond to public health emergencies.