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时间序列分析在阜阳市细菌性痢疾发病预测中的应用
引用本文:宁静,宋秀萍,孙良,田亚珍,梁长流,宁阳泉. 时间序列分析在阜阳市细菌性痢疾发病预测中的应用[J]. 安徽预防医学杂志, 2014, 20(3): 169-171
作者姓名:宁静  宋秀萍  孙良  田亚珍  梁长流  宁阳泉
作者单位:阜阳市疾病预防控制中心,安徽阜阳236030;阜阳市疾病预防控制中心,安徽阜阳236030;阜阳市疾病预防控制中心,安徽阜阳236030;阜阳市疾病预防控制中心,安徽阜阳236030;阜阳市疾病预防控制中心,安徽阜阳236030;阜阳市疾病预防控制中心,安徽阜阳236030
摘    要:目的探讨时间序列分析在细菌性痢疾发病预测中的应用,验证分析模型的可行性与适用性。方法利用阜阳市2009年1月~2013年6月细菌性痢疾发病资料,拟合自回归移动平均(ARIMA)模型,对阜阳市2013年7~11月各月发病情况进行预测评价。结果建立ARIMA(1,2,0)(0,1,0)12模型,预测结果基本符合实际发病变动趋势,验证了该模型的可行性。结论 ARIMA模型可用于模拟细菌性痢疾发病在时间序列上的变化趋势分析,并进行短期预测。

关 键 词:细菌性痢疾  时间序列分析  ARIMA模型

Applications of time series analysis to forecasting incidence of Bacillary Dysentery in Fuyang city
Affiliation:NING Jing, SONG Xiu - ping, SUN Liang, TIAN Ya - zhen, LIANG Chang - liu, NING Yang -quan ( Fuyang Center for Disease Con- trol and Prevention, Fuyang , Anhui 236030, China )
Abstract:Objective To explore the application of time series analysis to bacillary dysentery incidence forecasting and confirm its feasibility and applicability. Methods Autoregressive integrated moving average (ARIMA } model was fitted with data of monthly bacillary dysentery incidence from January 2009 to June 2013, and the monthly incidence of July to No- vember 2013 was predicted and evaluated. Results The model of ARIMA(1,2,0) × (0,1,0)12 was established,which was used to verify its feasibility due to predictive results were basic similar to actual incidence. Conclusion The model of ARIMA can be used to simulate variable trends of incidence for bacillary dysentery on time series and to forecast its prevalence within a short period.
Keywords:ARIMA  time series  tacillary dysentery
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