ARIMA模型在蚌埠市梅毒预测中的应用
|
摘要
目的:探讨时间序列分析中的乘积季节自回归移动平均(ARIMA)模型在蚌埠市梅毒发病率预测中应用的可行性,为制定梅毒防控措施提供参考依据方法:应用SPSS21.0软件对蚌埠市2008-2016年的梅毒发病率进行ARIMA模型拟合,依据BIC准则确定最优模型。用所得模型预测2017年1-6月的梅毒发病率,并与实际发病率进行比较,检验预测效果。结果:ARIMA(0,1,1)(1,0,0)12,可以较好地拟合梅毒月发病率规律,模型统计量Ljung-Box Q=16.726,P>0.05,残差序列为白噪声,用所得模型预测蚌埠市2017年1-6月梅毒月发病率,预测值与实际值吻合情况良好,实际值均在预测值的95%可信区间内。结论:ARIMA模型能较好拟合蚌埠市梅毒发病情况,对梅毒防治工作提供一定的参考价值。
Objective:To explore the feasibility of applying the seasonal autoregressive moving average(ARIMA) model for predicting the incidence of syphilis in Bengbu city,and provide reference in the prevention and control of syphilis.Methods:ARIMA model was used to fit the monthly incidence of syphilis in Bengbu from 2008 to 2016 by SPSS21.0 software,and the optimal model was established according to the BIC criterion.The incidence rate of syphilis from January to June 2017 was predicted,which was compared with the actual incidence in order to test the prediction effect.Results:The monthly incidence rate of syphilis was well fitted by ARIMA(0,1,1)(1,0,0)12.The model statistic Ljung-Box Q=16.726,P>0.05,and the residual sequence was white noise.The predictive value of syphilis incidence from January to June 2017 in Bengbu was well consistent with the actual value,and the actual values were within the 95% confidence interval of the predicted value.Conclusions:ARIMA model can well simulate the incidence of syphilis in Bengbu,and provide some reference basis for prevention and control of syphilis.
Objective:To explore the feasibility of applying the seasonal autoregressive moving average(ARIMA) model for predicting the incidence of syphilis in Bengbu city,and provide reference in the prevention and control of syphilis.Methods:ARIMA model was used to fit the monthly incidence of syphilis in Bengbu from 2008 to 2016 by SPSS21.0 software,and the optimal model was established according to the BIC criterion.The incidence rate of syphilis from January to June 2017 was predicted,which was compared with the actual incidence in order to test the prediction effect.Results:The monthly incidence rate of syphilis was well fitted by ARIMA(0,1,1)(1,0,0)12.The model statistic Ljung-Box Q=16.726,P>0.05,and the residual sequence was white noise.The predictive value of syphilis incidence from January to June 2017 in Bengbu was well consistent with the actual value,and the actual values were within the 95% confidence interval of the predicted value.Conclusions:ARIMA model can well simulate the incidence of syphilis in Bengbu,and provide some reference basis for prevention and control of syphilis.
引文
[1] AGRAWAL PG,JOSHI R,KHARKAR VD,et al.Congenital syphilis:the continuing scourge[J].Indian J Sex Transm Dis,2014,35(2):143.
[2] ZHANG W,DU Z,TANG S,et al.Syphilis in the economic center of South China:results from a real-time,web-based surveillance program[J].BMC Infect Dis,2015,15:318.
[3] 刘姝颖,李延庆,孟庆联,等.安徽省2004～2010年梅毒、淋病流行趋势分析[J].安徽医学,2012,33(2):220.
[4] 孙振球.医学统计学[M].4 版.北京:人民卫生出版社,2016:384.
[5] 中国人民银行调查统计司.时间序列 X-12-ARIM A 季节调整—原理与方法[M].北京:中国金融出版社,2006:59.
[6] BOX G,JENKINS G,GREGORY REINSEL,et al.时间序列分析预测与控制[M].北京:中国统计出版社,1997:377.
[7] 宇传华.SPSS与统计分析[M].北京:电子工业出版社,2014:593.
[8] 高云云,李军,杨海燕,等.ARIMA模型在河南省甲型病毒性肝炎发病数预测中的应用[J].现代预防医学,2017,44(7):1294.
[9] 马晓梅,刘颖,杨梦利,等.手足口病月发病率ARIMA乘积季节模型预测探讨[J].现代预防医学,2017,44(9):1541.
[10] 陈伟,陈正利,李少芳,等.ARIMA模型在河南省梅毒月发病率预测中的应用[J].中国卫生统计,2013,30(4):604.
[11] 胡冰雪,曲波,刘洁,等.中国 1990-2011 年梅毒流行特征分析与趋势预测[J].现代预防医学,2014,41(6):961.
[12] 王永斌,李向文,柴峰,等.ARIMA模型在我国梅毒发病率预测中的应用[J].现代预防医学,2015,42(3):385.
[13] 郭璐,张敏,朱正平,等.ARIMA模型在南京市梅毒预测中的应用[J].现代预防医学,2015,42(2):205.
[2] ZHANG W,DU Z,TANG S,et al.Syphilis in the economic center of South China:results from a real-time,web-based surveillance program[J].BMC Infect Dis,2015,15:318.
[3] 刘姝颖,李延庆,孟庆联,等.安徽省2004～2010年梅毒、淋病流行趋势分析[J].安徽医学,2012,33(2):220.
[4] 孙振球.医学统计学[M].4 版.北京:人民卫生出版社,2016:384.
[5] 中国人民银行调查统计司.时间序列 X-12-ARIM A 季节调整—原理与方法[M].北京:中国金融出版社,2006:59.
[6] BOX G,JENKINS G,GREGORY REINSEL,et al.时间序列分析预测与控制[M].北京:中国统计出版社,1997:377.
[7] 宇传华.SPSS与统计分析[M].北京:电子工业出版社,2014:593.
[8] 高云云,李军,杨海燕,等.ARIMA模型在河南省甲型病毒性肝炎发病数预测中的应用[J].现代预防医学,2017,44(7):1294.
[9] 马晓梅,刘颖,杨梦利,等.手足口病月发病率ARIMA乘积季节模型预测探讨[J].现代预防医学,2017,44(9):1541.
[10] 陈伟,陈正利,李少芳,等.ARIMA模型在河南省梅毒月发病率预测中的应用[J].中国卫生统计,2013,30(4):604.
[11] 胡冰雪,曲波,刘洁,等.中国 1990-2011 年梅毒流行特征分析与趋势预测[J].现代预防医学,2014,41(6):961.
[12] 王永斌,李向文,柴峰,等.ARIMA模型在我国梅毒发病率预测中的应用[J].现代预防医学,2015,42(3):385.
[13] 郭璐,张敏,朱正平,等.ARIMA模型在南京市梅毒预测中的应用[J].现代预防医学,2015,42(2):205.