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目的探索时间序列分析法在象山半岛水性疾病发病情况分析与预测中的应用。方法收集象山半岛地区2004—2013年水源性传染病病例信息,对发病趋势进行分析;运用时间序列分析法对水性疾病数据进行拟合,构建ARIMA时间序列分析模型,对发病情况进行预测。结果水性疾病发病呈长期递减以及季节变化趋势;对时间序列进行一阶差分提取趋势特征,再进行12步周期差分提取周期信息后,构建ARIMA(1,1,1)×(0,1,0)12模型,对2014年1—6月水性疾病发病数做预测,显示模型预测值与实际值呈现高度一致性。结论ARIMA模型可以对水性疾病发病进行有效预测。
Objective To explore the application of time series analysis in the analysis and prediction of waterborne diseases in Xiangshan Peninsula. Methods The information of cases of waterborne infectious diseases in Xiangshan Peninsula from 2004 to 2013 was collected to analyze the trend of incidence. The data of waterborne diseases were fitted by time series analysis, and ARIMA time series analysis model was constructed to predict the incidence. Results The incidence of waterborne diseases showed a long-term decline and the trend of seasonal changes. After the first-order differential extraction of the time series, the ARIMA (1,1,1) × (0,1,0 ) 12 model, forecast the incidence of waterborne diseases from January to June 2014, showing a high degree of consistency between predicted and actual values. Conclusion ARIMA model can effectively predict the incidence of waterborne diseases.