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has been cited by the following article:

• TITLE: A Visual Analysis and Prediction System for Infectious Diseases Based on Improved SIR Model

  AUTHORS: Yu Qiu, Yadong Wu, Qibiao Wang, Weihan Zhang

  KEYWORDS: Migration, Epidemic Forecast, Mi/Mo-SIR Model, Machine Learning, Visual Analytics System

  JOURNAL NAME: Journal of Computer and Communications, Vol.10 No.12, December 28, 2022

  ABSTRACT: To effectively track the impact of population migration between regions on the spread of infectious diseases, this paper proposes a visualized analysis and prediction system of infectious diseases based on the improved SIR model. The research contents including: using the multi graph link interaction mode, visualizing the space-time distribution and development trend of infectious diseases; The LightGBM model is used to track the changes of infection rate and recovery rate, and the Mi/Mo SIR model is constructed according to the initial data of different populations; Mi/Mo SIR model is used to predict infectious diseases in combination with visual panel, providing users with tools to analyze and explain the space-time characteristics and potential laws of infectious diseases. The study found that the closure of cities and the restriction of personnel mobility were necessary and effective, and the system provided an important basis for the prediction and early warning of infectious diseases.