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We predicts the future trends of Ebola. Following the SIR model, we construct the similar 'NSPC' model to describe the fluctuation of four classified cases. Because of the discreteness of data, we replace differential equations in the NSPC model with difference equations. Then according to historical data, we can adopt the nonlinear least squares method to obtain the spread equation and trend chart. 1. The Classification of the Crowd In order to develop a reliable plan of drug manufacturing and delivery, we first need to learn the spread of Ebola virus in the future few month. Furthermore, we need to claim that our prediction model is established on the basis of existing data. Namely, we are in the absence of effective drug and vaccine to make predictions. Obtaining the data from reliable resources (Wikipedia, the WHO's official website), we then divide the population into four categories according to the definition given by WHO. .

A Method about Ebola Spread Forecasts Based on SIR