摘要
目的构建北京市房山区感染性腹泻发病的季节性求和自回归移动平均(seasonal autoregressive integrated moving average,SARIMA)模型并进行预测。方法应用R 3.0.1软件程序包中的TSA对2004 2013年房山区感染性腹泻月发病率构建模型,并对2014年各月感染性腹泻月发病率进行预测和评价。结果 SARIMA(0,0,2)(0,1,1)12模型较好地拟合既往时间段月发病率,对2014年发病趋势拟合平均相对误差为19.164%,对年发病率拟合平均相对误差为2.303%。结论 SARIMA(0,0,2)(0,1,1)12模型能够很好拟合感染性腹泻月发病率数据,可用于房山区感染性腹泻发病趋势的短期预测,为下一步采取针对性防控措施提供科学依据。
Objective To establish a seasonal autoregressive integrated moving average（ SARIM A） model to predict the transmission trend of infectious diarrhea in Fangshan district of Beijing. Methods A SARIM A model was established based on the monthly incidence data of infectious diarrhea from 2004 to 2013 in Fangshan by using software R 3. 0. 1 TSA. We evaluated the fitting results of observed values and predicted values, and used this model to predict and analyze the transmission trend of infectious diarrhea by using the incidence data of infectious diarrhea in Fangshan from January to December 2014. Results SARIM A（ 0,0,2）（ 0,1,1）12was fitted well with the observed values. The average relative error of the model fitted to the selected actual case data was 19. 164%. The average relative error of the model in annual incidence was 2. 303%. Conclusion SARIM A（ 0,0,2）（ 0,1,1）12can be applied to predict short-term incidences of infectious diarrhea in Fangshan,which would provide scientific evidence for the evaluation of prevention and control of infectious diarrhea.
出处
《疾病监测》
CAS
2016年第2期136-140,共5页
Disease Surveillance
关键词
感染性腹泻
季节性求和自回归移动平均模型
时间序列分析
Infectious diarrhea
Seasonal autoregressive integrated moving average model
Time-series analysis
