Modeling Transmission Of Severe Acute Respiratory Syndrome

Sever Acute Respiratory Syndrome (SARS) which emerged in 2002 has huge influence on China's society and economy. When SARS breaks out again, if mathematics model can be established and simulates the development trand of SARS spreading, it makes important sense for controlling SARS and it is the basis of control policy adopted by the government and medical department.After studying many references about epidemic spreading, combining the existed motheds, models of SARS transmission and simulation system of SARS transmission based on these models are designed.In theory, three models about SARS transmission are established. Based on traditional SIR model, a new group F named free infective people is added . Free infective people is the origin of the epidemic, so controlling them can prevent the transmission of SARS. Simulation result proves this model is reasonable. The rule of SARS transmission is a complicated problem with nonlinear phenomenon. Neural network is a useful method for modelling nonlinear system. The second method of this paper makes use of advantage of neural network, and builds the model based on it. After building the structure of neural network, it is trained with reported data. Compared to reported data, the prediction result using the trained network is very accurate.The model of SARS transmission based on complex network is the most important in this paper, complex network is a new research field in the recent years, and sduty for SARS transmission on it is a new project. The tow-dimensional complex network in this paper has small characteristic path length,big clustering coefficient and power-law distrribution. SARS spreading in this network has been studied and some conclusions including long edges can quicken SARS transmission are obtained. Simulation results can explain the real data of Beijing.Three motheds are used in this paper to explore dynamic transmission of SARS, and simulation system of SARS transmission is developed. These work has very important meaning for controling SARS and orther similar epidemics.