赵梦娇, 于秋燕, 赵小冬, 许华茹, 徐淑慧. ARIMA季节乘积模型预测济南市猩红热发病趋势[J]. 疾病监测, 2016, 31(5): 411-415. DOI: 10.3784/j.issn.1003-9961.2016.05.014
引用本文: 赵梦娇, 于秋燕, 赵小冬, 许华茹, 徐淑慧. ARIMA季节乘积模型预测济南市猩红热发病趋势[J]. 疾病监测, 2016, 31(5): 411-415. DOI: 10.3784/j.issn.1003-9961.2016.05.014
ZHAO Meng-jiao, YU Qiu-yan, ZHAO Xiao-dong, XU Hua-ru, XU Shu-hui. Application of ARIMA model for prediction of incidence of scarlet fever[J]. Disease Surveillance, 2016, 31(5): 411-415. DOI: 10.3784/j.issn.1003-9961.2016.05.014
Citation: ZHAO Meng-jiao, YU Qiu-yan, ZHAO Xiao-dong, XU Hua-ru, XU Shu-hui. Application of ARIMA model for prediction of incidence of scarlet fever[J]. Disease Surveillance, 2016, 31(5): 411-415. DOI: 10.3784/j.issn.1003-9961.2016.05.014

ARIMA季节乘积模型预测济南市猩红热发病趋势

Application of ARIMA model for prediction of incidence of scarlet fever

  • 摘要: 目的 探讨ARIMA季节乘积模型在济南市猩红热月发病率预测中的应用,并预测猩红热月发病趋势,为制订防控策略提供依据。方法 对济南市2006-2014年猩红热月发病率资料建立ARIMA季节乘积模型,利用2015年1-6月发病资料检验模型的精度,并预测2015年各月发病率。结果 构建ARIMA(1,0,0)(0,1,1)12模型可以用于济南市猩红热月发病率的拟合和预测,模型决定系数R2=0.64。结论 2015年济南市猩红热处于高流行期,应警惕出现流行和暴发的可能,在高发时间、高发地点做好猩红热的监测和应对工作,防止暴发流行。

     

    Abstract: Objective To evaluate the performance of multiple seasonal autoregressive integrated moving average (ARIMA) model in the prediction of scarlet fever incidence in Jinan, and provide evidence for the prevention and control of the disease. Methods The incidence data of scarlet fever in Jinan from 2006 to 2014 were used to establish ARIMA model and the incidence data in Jinan from January to June in 2015 were used to evaluate the accuracy of the model. The incidence of scarlet fever in Jinan in 2105 was predicted by using the model. Results ARIMA (1,0,0)(0,1,1)12 model could be used to predict epidemiological tendency of scarlet fever in Jinan. The R2 of the model was 0.64. Conclusion The incidence of scarlet fever in Jinan was still at high level in 2015. It is necessary to strengthen the scarlet fever surveillance to prevent the outbreak of scarlet fever.

     

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