IDEAS home Printed from https://ideas.repec.org/a/spr/fuzodm/v20y2021i2d10.1007_s10700-020-09342-9.html
   My bibliography  Save this article

Numerical solution and parameter estimation for uncertain SIR model with application to COVID-19

Author

Listed:
  • Xiaowei Chen

    (Nankai University)

  • Jing Li

    (Nankai University)

  • Chen Xiao

    (Nankai University)

  • Peilin Yang

    (Nankai University)

Abstract

Developing algorithms for solving high-dimensional uncertain differential equations has been an exceedingly difficult task. This paper presents an $$\alpha $$ α -path-based approach that can handle the proposed high-dimensional uncertain SIR model. We apply the $$\alpha $$ α -path-based approach to calculating the uncertainty distributions and related expected values of the solutions. Furthermore, we employ the method of moments to estimate parameters and design a numerical algorithm to solve them. This model is applied to describing the development trend of COVID-19 using infected and recovered data of Hubei province. The results indicate that lockdown policy achieves almost 100% efficiency after February 13, 2020, which is consistent with the existing literatures. The high-dimensional $$\alpha $$ α -path-based approach opens up new possibilities in solving high-dimensional uncertain differential equations and new applications.

Suggested Citation

  • Xiaowei Chen & Jing Li & Chen Xiao & Peilin Yang, 2021. "Numerical solution and parameter estimation for uncertain SIR model with application to COVID-19," Fuzzy Optimization and Decision Making, Springer, vol. 20(2), pages 189-208, June.
  • Handle: RePEc:spr:fuzodm:v:20:y:2021:i:2:d:10.1007_s10700-020-09342-9
    DOI: 10.1007/s10700-020-09342-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10700-020-09342-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10700-020-09342-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhiming Li & Zhidong Teng, 2019. "Analysis of uncertain SIS epidemic model with nonlinear incidence and demography," Fuzzy Optimization and Decision Making, Springer, vol. 18(4), pages 475-491, December.
    2. Yang, Xiangfeng & Liu, Yuhan & Park, Gyei-Kark, 2020. "Parameter estimation of uncertain differential equation with application to financial market," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    3. Jayson S. Jia & Xin Lu & Yun Yuan & Ge Xu & Jianmin Jia & Nicholas A. Christakis, 2020. "Population flow drives spatio-temporal distribution of COVID-19 in China," Nature, Nature, vol. 582(7812), pages 389-394, June.
    4. Kai Yao & Baoding Liu, 2020. "Parameter estimation in uncertain differential equations," Fuzzy Optimization and Decision Making, Springer, vol. 19(1), pages 1-12, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gao, Yin & Gao, Jinwu & Yang, Xiangfeng, 2022. "The almost sure stability for uncertain delay differential equations based on normal lipschitz conditions," Applied Mathematics and Computation, Elsevier, vol. 420(C).
    2. He, Liu & Zhu, Yuanguo, 2024. "Nonparametric estimation for uncertain fractional differential equations," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    3. Liu He & Yuanguo Zhu & Ziqiang Lu, 2023. "Parameter estimation for uncertain fractional differential equations," Fuzzy Optimization and Decision Making, Springer, vol. 22(1), pages 103-122, March.
    4. Tang, Han & Yang, Xiangfeng, 2021. "Uncertain chemical reaction equation," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    5. Shami, Labib & Lazebnik, Teddy, 2022. "Economic aspects of the detection of new strains in a multi-strain epidemiological–mathematical model," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    6. Yang Liu & Baoding Liu, 2022. "Residual analysis and parameter estimation of uncertain differential equations," Fuzzy Optimization and Decision Making, Springer, vol. 21(4), pages 513-530, December.
    7. Liu He & Yuanguo Zhu & Yajing Gu, 2023. "Nonparametric estimation for uncertain differential equations," Fuzzy Optimization and Decision Making, Springer, vol. 22(4), pages 697-715, December.
    8. Zhangbo Yang & Jiahao Zhang & Shanxing Gao & Hui Wang, 2022. "Complex Contact Network of Patients at the Beginning of an Epidemic Outbreak: An Analysis Based on 1218 COVID-19 Cases in China," IJERPH, MDPI, vol. 19(2), pages 1-17, January.
    9. Chen, Dan & Liu, Yang, 2023. "Uncertain Gordon-Schaefer model driven by Liu process," Applied Mathematics and Computation, Elsevier, vol. 450(C).
    10. Vahdani, Behnam & Mohammadi, Mehrdad & Thevenin, Simon & Meyer, Patrick & Dolgui, Alexandre, 2023. "Production-sharing of critical resources with dynamic demand under pandemic situation: The COVID-19 pandemic," Omega, Elsevier, vol. 120(C).
    11. Farshid Mehrdoust & Idin Noorani & Wei Xu, 2023. "Uncertain energy model for electricity and gas futures with application in spark-spread option price," Fuzzy Optimization and Decision Making, Springer, vol. 22(1), pages 123-148, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lifen Jia & Wei Chen, 2021. "Uncertain SEIAR model for COVID-19 cases in China," Fuzzy Optimization and Decision Making, Springer, vol. 20(2), pages 243-259, June.
    2. Najafi, Alireza & Taleghani, Rahman, 2022. "Fractional Liu uncertain differential equation and its application to finance," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    3. Pan, Zeyu & Gao, Yin & Yuan, Lin, 2021. "Bermudan options pricing formulas in uncertain financial markets," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    4. Jie, Ke-Wei & Liu, San-Yang & Sun, Xiao-Jun & Xu, Yun-Cheng, 2023. "A dynamic ripple-spreading algorithm for solving mean–variance of shortest path model in uncertain random networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    5. Chen, Dan & Liu, Yang, 2023. "Uncertain Gordon-Schaefer model driven by Liu process," Applied Mathematics and Computation, Elsevier, vol. 450(C).
    6. Jin, Ting & Yang, Xiangfeng, 2021. "Monotonicity theorem for the uncertain fractional differential equation and application to uncertain financial market," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 203-221.
    7. Liu, Z. & Yang, Y., 2021. "Selection of uncertain differential equations using cross validation," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    8. Zhang, Guidong & Sheng, Yuhong, 2022. "Estimating time-varying parameters in uncertain differential equations," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    9. Tingqing Ye & Baoding Liu, 2023. "Uncertain hypothesis test for uncertain differential equations," Fuzzy Optimization and Decision Making, Springer, vol. 22(2), pages 195-211, June.
    10. Chen, Xin & Zhu, Yuanguo & Sheng, Linxue, 2021. "Optimal control for uncertain stochastic dynamic systems with jump and application to an advertising model," Applied Mathematics and Computation, Elsevier, vol. 407(C).
    11. Tang, Han & Yang, Xiangfeng, 2022. "Moment estimation in uncertain differential equations based on the Milstein scheme," Applied Mathematics and Computation, Elsevier, vol. 418(C).
    12. Waichon Lio & Baoding Liu, 2021. "Initial value estimation of uncertain differential equations and zero-day of COVID-19 spread in China," Fuzzy Optimization and Decision Making, Springer, vol. 20(2), pages 177-188, June.
    13. Waichon Lio & Rui Kang, 2023. "Bayesian rule in the framework of uncertainty theory," Fuzzy Optimization and Decision Making, Springer, vol. 22(3), pages 337-358, September.
    14. Noorani, Idin & Mehrdoust, Farshid, 2022. "Parameter estimation of uncertain differential equation by implementing an optimized artificial neural network," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    15. Zhiyong Huang & Chunliu Zhu & Jinwu Gao, 2021. "Stability analysis for uncertain differential equation by Lyapunov’s second method," Fuzzy Optimization and Decision Making, Springer, vol. 20(1), pages 129-144, March.
    16. Wang, Weiwei & Ralescu, Dan A., 2021. "Valuation of lookback option under uncertain volatility model," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    17. Gao, Yin & Gao, Jinwu & Yang, Xiangfeng, 2022. "Parameter estimation in uncertain delay differential equations via the method of moments," Applied Mathematics and Computation, Elsevier, vol. 431(C).
    18. Lu Yang & Tingqing Ye & Haizhong Yang, 2022. "Uncertain seepage equation in fissured porous media," Fuzzy Optimization and Decision Making, Springer, vol. 21(3), pages 383-403, September.
    19. Jia, Lifen & Chen, Wei, 2020. "Knock-in options of an uncertain stock model with floating interest rate," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    20. Sheng, Yuhong & Yao, Kai & Qin, Zhongfeng, 2020. "Continuity and variation analysis of fractional uncertain processes," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:fuzodm:v:20:y:2021:i:2:d:10.1007_s10700-020-09342-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.