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The Comparison of ARMA, Exponential Smoothing and Seasonal IndexModel for Predicting Incidence of Newcastle Disease

机译：ARMA，指数平滑和季节性指数的比较预测新城疫发病率

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The mathematical model prediction has been widely recognized among many disease forecasting methods. But different models will show out distinct prediction results of different diseases, as well as their occurrence locations. In this study, ARMA, exponential smoothing and seasonal index model were adopted for predicting incidence of Newcastle disease, and evaluating the precision of these three models. A predictive model was confirmed for the occurrence of Newcastle disease in the province A of China, through comparing with the three mathematical models. Method: ARMA, exponential smoothing and seasonal index model were established and fitted according to the incidence of Newcastle disease in province A from Jan. 2000 to Dec. 2007. Meanwhile, used the three models to predict the incidence of Newcastle disease in province A from Jan. 2008 to Dec. 2008 and then compared their effect of fitting and prediction. The results showed that the predictive value of ARMA model was most close to the true number, and has the fittest predicting effect. The method of quantitative predictions was used in numerically simulating the incidence of Newcastle disease, which can reflect the transmitting tendency and incidence of Newcastle disease in recently years and provide theoretical basis for constituting optimum preventive strategies.
机译：在许多疾病预测方法中，数学模型预测已被广泛认识到。但不同的模型将展示不同疾病的不同预测结果，以及它们的出现位置。在本研究中，采用ARMA，指数平滑和季节性指数模型来预测新城疫的发病率，并评估这三种模型的精度。通过与三个数学模型的比较，确认了在中国省A中新城疫的发生的预测模型。方法：建立了ARMA，指数平滑和季节性指数模型，根据2000年1月至12月至2007年12月的新城疫发病率。与此同时，使用这三种模型预测省A来自省份的新城疫发病率2008年1月至2008年12月，然后比较了它们对拟合和预测的影响。结果表明，ARMA模型的预测值最接近真实数，具有最适合的预测效果。定量预测方法在数值上模拟了新城疫疾病的发生率，这可以反映近年来新城疫的传播趋势和发病率，为构成最佳预防策略提供理论依据。

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