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Time Prediction Models for Echinococcosis Based on Gray System Theory and Epidemic Dynamics

Author

Listed:
  • Liping Zhang

    (College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830011, China
    These authors contributed equally to this work.)

  • Li Wang

    (College of Public Health, Xinjiang Medical University, Urumqi 830011, China
    These authors contributed equally to this work.)

  • Yanling Zheng

    (College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830011, China)

  • Kai Wang

    (College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830011, China)

  • Xueliang Zhang

    (College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830011, China)

  • Yujian Zheng

    (College of Public Health, Xinjiang Medical University, Urumqi 830011, China)

Abstract

Echinococcosis, which can seriously harm human health and animal husbandry production, has become an endemic in the Xinjiang Uygur Autonomous Region of China. In order to explore an effective human Echinococcosis forecasting model in Xinjiang, three grey models, namely, the traditional grey GM(1,1) model, the Grey-Periodic Extensional Combinatorial Model (PECGM(1,1)), and the Modified Grey Model using Fourier Series (FGM(1,1)), in addition to a multiplicative seasonal ARIMA(1,0,1)(1,1,0) 4 model, are applied in this study for short-term predictions. The accuracy of the different grey models is also investigated. The simulation results show that the FGM(1,1) model has a higher performance ability, not only for model fitting, but also for forecasting. Furthermore, considering the stability and the modeling precision in the long run, a dynamic epidemic prediction model based on the transmission mechanism of Echinococcosis is also established for long-term predictions. Results demonstrate that the dynamic epidemic prediction model is capable of identifying the future tendency. The number of human Echinococcosis cases will increase steadily over the next 25 years, reaching a peak of about 1250 cases, before eventually witnessing a slow decline, until it finally ends.

Suggested Citation

  • Liping Zhang & Li Wang & Yanling Zheng & Kai Wang & Xueliang Zhang & Yujian Zheng, 2017. "Time Prediction Models for Echinococcosis Based on Gray System Theory and Epidemic Dynamics," IJERPH, MDPI, vol. 14(3), pages 1-14, March.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:3:p:262-:d:92157
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    References listed on IDEAS

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    Cited by:

    1. Gong, Wei & Wang, Zhanping, 2023. "Sliding motion control of Echinococcosis transmission dynamics model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 205(C), pages 468-482.
    2. Yu-Feng Zhao & Ming-Huan Shou & Zheng-Xin Wang, 2020. "Prediction of the Number of Patients Infected with COVID-19 Based on Rolling Grey Verhulst Models," IJERPH, MDPI, vol. 17(12), pages 1-20, June.
    3. Qingwei Xu & Kaili Xu, 2020. "Statistical Analysis and Prediction of Fatal Accidents in the Metallurgical Industry in China," IJERPH, MDPI, vol. 17(11), pages 1-20, May.

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