利用灰色残差法GM模型预测广东省细菌性痢疾发病趋势

Prediction of epidemic tendency of bacillary dysentery in Guangdong Province by using gray residual GM model

目的探讨利用滑动平均法和灰色残差法GM模型建立预测预警模型,并预测广东省细菌性痢疾发病趋势,为今后防治提供科学的数据依据。方法对广东省2004—2011年细菌性痢疾的发病数据进行整理、分析,建立基于滑动平均法的灰色残差法GM模型(III型),并对传统灰色GM模型(Ⅰ型)、基于滑动平均法的灰色GM模型(Ⅱ型)分别以平均相对误差、后验差、小误差概率作为检验指标进行对比分析。结果采用模型(Ⅰ、Ⅱ、III型)进行实例预测分析,经过精度指标检验结果分别为:模型Ⅰ:C=0.39,P=1.00,模型精度为2级(良),平均相对误差ψ=8.86%;模型Ⅱ:C=0.34,P=1.00,模型精度为1级(优),平均相对误差ψ=7.53%;模型III:C=0.22,P=1.00,模型精度为1级(优),平均相对误差ψ=5.21%。由此得出,模型III较模型(Ⅰ、Ⅱ)在模型精度等级及平均相对误差相对比较小。运用模型Ⅲ对广东省2012、2013、2014年细菌性痢疾的发病率进行预测,结果为5.069 3/10万、4.514 0/10万、4.027 0/10万。结论经过3种模型的对比分析结果表明:基于滑动平均法的灰色残差法GM模型(III型)的拟合精度很高,最终验证了该模型应用于广东省在细菌性痢疾疫情预测方面的可行性及有效性,为预测细菌性痢疾发病趋势提供依据。

Objective Through exploring the use of the moving average method and gray residual GM model to establish prediction early warning model and predict the epidemic tendency of bacillary dysen- tery in Gnangdong Province, to provide scientific database for future prevention and control. Methods Bacillary dysentery incidence data in 2004 -2011 in Guangdong Province were collected. We established Gray residual GM Model based on the moving average method （Type Ⅲ） and adopted the average relative error, posterior difference, and small error probability as the test indicators to compare and analyze the tra- ditional gray GM model （Type Ⅰ） and Gray GM model based on the moving average method （Type Ⅱ ）. Results The results showed that ： C = 0.22, P = 1.00, the accuracy of the model （ Type Ⅲ） is 1 （good）, the average relative error is 5.21%. The model level and average relative error of Model （Type Ⅲ） is relatively small compared with the other two models （types Ⅰ and Ⅱ）. The estimates of incidence of bacillary dysentery in Guangdong Province in 2012, 2013, and 2014 using model （Type Ⅲ） are 5. 069 3/100 000, 4.514 0/100 000 and 4.027 0/100 000, respectively. Conclusion Gray residual GM model based on the moving average method （Type Ⅲ） has the highest fitting accuracy compared with the other two models. It provides the evidence of feasibility and effectiveness to predict the epidemic tendency of bacillary dysentery in Guangdong Province.