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CN 34-1304/RISSN 1674-3679

Volume 23 Issue 11
Nov.  2019
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XIONG Yu-yang, REN Jing-chao, DUAN Guang-cai. Application of the time series model in prediction of incidence of hand-foot-mouth disease from 2008 to 2016 in China[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2019, 23(11): 1394-1398. doi: 10.16462/j.cnki.zhjbkz.2019.11.019
Citation: XIONG Yu-yang, REN Jing-chao, DUAN Guang-cai. Application of the time series model in prediction of incidence of hand-foot-mouth disease from 2008 to 2016 in China[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2019, 23(11): 1394-1398. doi: 10.16462/j.cnki.zhjbkz.2019.11.019

Application of the time series model in prediction of incidence of hand-foot-mouth disease from 2008 to 2016 in China

doi: 10.16462/j.cnki.zhjbkz.2019.11.019
Funds:

National Natural Science Foundation of China 81573205

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  • Corresponding author: DUAN Guang-cai, E-mail: gcduan@zzu.edu.cn
  • Received Date: 2019-07-02
  • Rev Recd Date: 2019-09-12
  • Publish Date: 2019-11-10
  •   Objective  To predict the monthly incidence of hand-foot-mouth disease (HFMD) in China by using autoregressive integrated moving average (ARIMA) model and provide evidence for prevention and control of HFMD.  Methods  The monthly incidence data of HFMD in China from 2008 to 2016 were collected from the Public Health Science data Center. The incidence database was established by Excel 2007 and graphed. SAS 9.1 was used to construct the ARIMA model, based on the data of the monthly reported incidence of HFMD in China from January 2008 to December 2015, and then the data in 2016 were used to verify the predicted results. The monthly incidence in 2017 was predicted in the same way.The difference was statistically significant when P<0.05.  Result  The model predicting monthly incidence of HFMD in China is ARIMA ((12), 2, 0) sparse coefficient and residuals is white noise. The parameters were as follows: moted mean squared error=3.6490, mean absolute error=2.62, mean absolute percentage error=28.24%.  Conclusion  The sparse coefficient model could well simulate the trend of HFMD case in time series, which has good reference of early warning and prevention of HFMD.
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