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CN 34-1304/RISSN 1674-3679

Volume 23 Issue 8
Aug.  2019
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LIU Li-jun, LIU Yu, ZHOU Xing-yu, ZHANG Jia-ke, LI Wei, QI Qi. Analysis of epidemiological characteristics of Japanese encephalitis in Sichuan Province from 2008 to 2018 and application of autoregressive integrated moving average model[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2019, 23(8): 916-921. doi: 10.16462/j.cnki.zhjbkz.2019.08.007
Citation: LIU Li-jun, LIU Yu, ZHOU Xing-yu, ZHANG Jia-ke, LI Wei, QI Qi. Analysis of epidemiological characteristics of Japanese encephalitis in Sichuan Province from 2008 to 2018 and application of autoregressive integrated moving average model[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2019, 23(8): 916-921. doi: 10.16462/j.cnki.zhjbkz.2019.08.007

Analysis of epidemiological characteristics of Japanese encephalitis in Sichuan Province from 2008 to 2018 and application of autoregressive integrated moving average model

doi: 10.16462/j.cnki.zhjbkz.2019.08.007
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  • Corresponding author: QI Qi. E-mail: 250877069@qq.com
  • Received Date: 2019-02-14
  • Rev Recd Date: 2019-06-10
  • Publish Date: 2019-08-10
  •   Objective  The aim is to describe the epidemiological characteristics of Japanese encephalitis(JE) in Sichuan Province from 2008 to 2018, to build time series autoregressive integrated moving average(ARIMA) model, and to discuss the model application in the prediction of JE incidence trends.  Methods  Descriptive epidemiological analysis was used to analyze the epidemic situation of JE in Sichuan Province from 2008 to 2018. Monthly surveillance data of JE in Sichuan Province from January 2008 to December 2017 were used to fit ARIMA model. The number of reported cases from January to December in 2018 was used to test the model.  Results  The epidemic situation of JE in Sichuan Province from 2008 to 2018 showed a downward trend, and eastern and southern areas were the highly prevalent areas. The incidence peak was from July to September every year. Children were the high-risk group, but the incidence of adolescent and adult was on the rise in recent years. ARIMA(1, 0, 0)(2, 1, 0)12 could appropriately fit the time series.  Conclusion  ARIMA model can be used for short-term prediction of the reported incidence of JE in Sichuan Province.
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