深圳市肾综合征出血热时间序列预测分析

目的利用拟合ARIMA模型对深圳市肾综合征出血热(HFRS)的发病趋势进行时间序列分析和预测,为制定HFRS防治策略提供科学依据。方法收集深圳市2005—2014年HFRS季度发病资料,通过SPSS 19.0软件拟合ARIMA模型,预测2015年各季度的发病数。结果最终拟合为ARIMA(0,0,0)(0,1,1)4模型,残差为白噪声序列,预测值与实际值的平均相对误差为28.6%。2015年各季度HFRS发病的预测值符合实际值的变动趋势。结论 ARIMA模型能较好模拟深圳市HFRS的发病趋势。

Time series predicting the epidemic tendency of HFRS in Shenzhen

Objective To analyze and predict incidence of hemorrhagic fever with renal syndrome (HFRS) in Shenzhen with an auto regressive integrated moving average (ARIMA) model, which may provide a scientific basis for developing prevention and control strategies on HFRS in the future. Methods Incidence of HFRS was collected quarterly from 2005 to 2014 and a model (ARIMA) was fit with SPSS 19.0 software, to predict the incidence of HFRS from the I quarter to IV quarter 2015.Results The model ARIMA (0, 0, 0) ( 0, 1, 0) 4 was established finally and the residual sequence was a white noise sequence. The relative error in average was 28.6% between the forecasting value and the real value. The predicted incidence in 2015 was consistent with the actual one. Conclusion ARIMA model can predict the trend of HFRS in Shenzhen.