SARIMA模型在新疆布鲁氏菌病发病预测中的应用

Application of SARIMA Model in Prediction of Brucellosis in Xinjiang

摘要: 本文收集了2004年1月~2016年12月的新疆布病的月发病数，通过对数据进行序列平稳化、模型识别、模型检验的处理，预测了2017年12个月的布病发病数，拟合了2016年2月~12月的值，并与2016年2月~12月的实际值比较，最终建立了SARIMA(1,1,0)(0,1,0)12模型(AIC = 1606.44)，具有较高的有效性和合理性，该模型较好地拟合了新疆布病的新发病数，认为SARIMA模型可用于布病的短期预测和有效预防。

Abstract: In order to fit the new incidence of brucellosis in Xinjiang, this paper uses ARIMA(P,D,q)(P,D,Q)12 model to make short-term prediction and discusses the feasibility of the model. This paper collects the monthly incidence of human brucellosis in Xinjiang from January 2004 to December 2016, and uses R software to find the optimal model and make prediction. First, the incidence of brucellosis in the 12 months of 2017 is predicted. Secondly, the value from February to December 2016 is fitted, and compared with the actual value from February to December 2016, the ARIMA(1,1,0)(0,1,0)12 model (AIC = 1606.44) is finally established, which has higher effectiveness and rationality. The model fits the new incidence of human brucellosis in Xinjiang well, and can be used for short-term prediction and effective prevention of brucellosis.