自回归综合移动平均模型预测全国手足口病月报告重症病例的研究

Shunxian Zhang, Qi Qiu, Ying Wang
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引用次数: 0

摘要

采用自回归综合移动平均(ARIMA)模型对中国手足口病(手足口病)月报告重症病例进行预测,为手足口病的预防和控制以及ARIMA在手足口病及其他传染病中的应用提供参考。时间序列的基础上提供的月度报告全国手足口病重症病例从2010 ~ 2015年,建立了ARIMA模型与实际的手足口病病例从2016年1月至9月的验证数据和比较ARIMA模型基于从2010 - 2014的数据模型基于2010 ~ 2014和2010 ~ 2015年的数据的月度报告严重的手足口病在中国ARIMA (1 1 0) (2 1 0) (12), ARIMA(0, 1, 1),(2, 1, 0)(12)。两种模型的比较表明,相对误差的平均值随累积数据的增加而减小,但随预测时间的缩短而变化不大。对于相同的传染病,不同的时间序列可能有不同的ARIMA模型。需要进一步验证的是,累积的数据越多,预测时间越短,相对误差的平均值越小。
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Study on the National Monthly Reported Severe Cases of Hand-foot-mouth Disease Forecasted by Autoregressive Integrated Moving Average Model.

Autoregressive integrated moving average (ARIMA) model was used to predict the monthly reported severe cases of hand-foot-mouth disease(HFMD) in China to provide a reference for prevention and control of HFMD and the application of ARIMA in of ARIMA in HFMD and other infectious diseases. On the basis of time series supplied by the monthly reported severe cases of the national HFMD from 2010 ~ 2015, ARIMA model was established with the actual cases of HFMD from January to September 2016 as the validated data and with the comparison of ARIMA model based on the data from 2010-2014- The models based on the 2010~2014 and 2010~2015 data of monthly reported severe cases of HFMD in China are ARIMA(1,1,0,) (2, 1,0)(12),ARIMA(0,1,1,) (2,1,0)(12) respectively. The comparison of two models shows that the average of the relative error decreases with the accumulated data and does not do the same with the shorter time of predication. Different time series may have different ARIMA models as for the same infectious diseases. It is needed to be further verified that the more data are accumulated, the more shorter time of predication is, the more-smaller the average of the relative error is.

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