ARIMA模型在蚌埠市梅毒预测中的应用

朱乐乐; 沈雁; 王祥; 吴学森

doi:10.13898/j.cnki.issn.1000-2200.2019.03.028

ARIMA模型在蚌埠市梅毒预测中的应用

Application value of ARIMA model in the prediction of syphilis in Bengbu city

摘要

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。

Abstract:
ObjectiveTo 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.
MethodsARIMA 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.
ResultsThe 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.
ConclusionsARIMA model can well simulate the incidence of syphilis in Bengbu, and provide some reference basis for prevention and control of syphilis.

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