Forecasting hand-foot-and-mouth disease cases using wavelet-based SARIMA-NNAR hybrid model.

Journal: PloS one
Published Date: Jan 1, 2021

Abstract

BACKGROUND: Hand-foot-and-mouth disease_(HFMD) is one of the most typical diseases in children that is associated with high morbidity. Reliable forecasting is crucial for prevention and control. Recently, hybrid models have become popular, and wavelet analysis has been widely performed. Better prediction accuracy may be achieved using wavelet-based hybrid models. Thus, our aim is to forecast number of HFMD cases with wavelet-based hybrid models.

Authors

  • Gongchao Yu
    Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
  • Huifen Feng
    Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
  • Shuang Feng
    Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
  • Jing Zhao
    Department of Pharmacy, Pharmacoepidemiology and Drug Safety Research Group, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway.
  • Jing Xu
    First Department of Infectious Diseases, The First Affiliated Hospital of China Medical University, Shenyang, China.

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