IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i12p1321-d570981.html
   My bibliography  Save this article

A Novel Technique to Control the Accuracy of a Nonlinear Fractional Order Model of COVID-19: Application of the CESTAC Method and the CADNA Library

Author

Listed:
  • Samad Noeiaghdam

    (Industrial Mathematics Laboratory, Baikal School of BRICS, Irkutsk National Research Technical University, 664074 Irkutsk, Russia
    Department of Applied Mathematics and Programming, South Ural State University, Lenin Prospect 76, 454080 Chelyabinsk, Russia)

  • Sanda Micula

    (Department of Mathematics and Computer Science, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania)

  • Juan J. Nieto

    (Instituto de Matemáticas, Departamento de Estatística, Análise Matemática e Optimización, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain)

Abstract

In this paper, a nonlinear fractional order model of COVID-19 is approximated. For this aim, at first we apply the Caputo–Fabrizio fractional derivative to model the usual form of the phenomenon. In order to show the existence of a solution, the Banach fixed point theorem and the Picard–Lindelof approach are used. Additionally, the stability analysis is discussed using the fixed point theorem. The model is approximated based on Indian data and using the homotopy analysis transform method (HATM), which is among the most famous, flexible and applicable semi-analytical methods. After that, the CESTAC (Controle et Estimation Stochastique des Arrondis de Calculs) method and the CADNA (Control of Accuracy and Debugging for Numerical Applications) library, which are based on discrete stochastic arithmetic (DSA), are applied to validate the numerical results of the HATM. Additionally, the stopping condition in the numerical algorithm is based on two successive approximations and the main theorem of the CESTAC method can aid us analytically to apply the new terminations criterion instead of the usual absolute error that we use in the floating-point arithmetic (FPA). Finding the optimal approximations and the optimal iteration of the HATM to solve the nonlinear fractional order model of COVID-19 are the main novelties of this study.

Suggested Citation

  • Samad Noeiaghdam & Sanda Micula & Juan J. Nieto, 2021. "A Novel Technique to Control the Accuracy of a Nonlinear Fractional Order Model of COVID-19: Application of the CESTAC Method and the CADNA Library," Mathematics, MDPI, vol. 9(12), pages 1-26, June.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:12:p:1321-:d:570981
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/12/1321/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/12/1321/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Naik, Parvaiz Ahmad & Zu, Jian & Owolabi, Kolade M., 2020. "Global dynamics of a fractional order model for the transmission of HIV epidemic with optimal control," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    2. Naik, Parvaiz Ahmad & Zu, Jian & Owolabi, Kolade M., 2020. "Modeling the mechanics of viral kinetics under immune control during primary infection of HIV-1 with treatment in fractional order," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    3. Vignes, J., 1993. "A stochastic arithmetic for reliable scientific computation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 35(3), pages 233-261.
    4. Galanis, Giorgos & Hanieh, Adam, 2021. "Incorporating Social Determinants of Health into Modelling of COVID-19 and other Infectious Diseases: A Baseline Socio-economic Compartmental Model," Social Science & Medicine, Elsevier, vol. 274(C).
    5. Sarkar, Kankan & Khajanchi, Subhas & Nieto, Juan J., 2020. "Modeling and forecasting the COVID-19 pandemic in India," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    6. Panwar, Virender Singh & Sheik Uduman, P.S. & Gómez-Aguilar, J.F., 2021. "Mathematical modeling of coronavirus disease COVID-19 dynamics using CF and ABC non-singular fractional derivatives," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    7. Günerhan, Hatıra & Dutta, Hemen & Dokuyucu, Mustafa Ali & Adel, Waleed, 2020. "Analysis of a fractional HIV model with Caputo and constant proportional Caputo operators," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    8. Ndaïrou, Faïçal & Area, Iván & Nieto, Juan J. & Silva, Cristiana J. & Torres, Delfim F.M., 2021. "Fractional model of COVID-19 applied to Galicia, Spain and Portugal," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    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. Agrawal, Khushbu & Kumar, Ranbir & Kumar, Sunil & Hadid, Samir & Momani, Shaher, 2022. "Bernoulli wavelet method for non-linear fractional Glucose–Insulin regulatory dynamical system," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    2. Baba, Isa Abdullahi & Rihan, Fathalla A., 2022. "A fractional–order model with different strains of COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).

    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. Samad Noeiaghdam & Aliona Dreglea & Hüseyin Işık & Muhammad Suleman, 2021. "A Comparative Study between Discrete Stochastic Arithmetic and Floating-Point Arithmetic to Validate the Results of Fractional Order Model of Malaria Infection," Mathematics, MDPI, vol. 9(12), pages 1-17, June.
    2. Abidemi, Afeez & Owolabi, Kolade M. & Pindza, Edson, 2022. "Modelling the transmission dynamics of Lassa fever with nonlinear incidence rate and vertical transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).
    3. Naik, Parvaiz Ahmad & Owolabi, Kolade M. & Yavuz, Mehmet & Zu, Jian, 2020. "Chaotic dynamics of a fractional order HIV-1 model involving AIDS-related cancer cells," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    4. Rubayyi T. Alqahtani & Abdelhamid Ajbar, 2021. "Study of Dynamics of a COVID-19 Model for Saudi Arabia with Vaccination Rate, Saturated Treatment Function and Saturated Incidence Rate," Mathematics, MDPI, vol. 9(23), pages 1-13, December.
    5. Mangal, Shiv & Misra, O.P. & Dhar, Joydip, 2023. "Fractional-order deterministic epidemic model for the spread and control of HIV/AIDS with special reference to Mexico and India," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 210(C), pages 82-102.
    6. Baba, Isa Abdullahi & Rihan, Fathalla A., 2022. "A fractional–order model with different strains of COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    7. Samad Noeiaghdam & Denis Sidorov & Alyona Zamyshlyaeva & Aleksandr Tynda & Aliona Dreglea, 2020. "A Valid Dynamical Control on the Reverse Osmosis System Using the CESTAC Method," Mathematics, MDPI, vol. 9(1), pages 1-17, December.
    8. Arshad, Sadia & Siddique, Imran & Nawaz, Fariha & Shaheen, Aqila & Khurshid, Hina, 2023. "Dynamics of a fractional order mathematical model for COVID-19 epidemic transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    9. Tyagi, Swati & Martha, Subash C. & Abbas, Syed & Debbouche, Amar, 2021. "Mathematical modeling and analysis for controlling the spread of infectious diseases," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    10. Hwang, Eunju, 2022. "Prediction intervals of the COVID-19 cases by HAR models with growth rates and vaccination rates in top eight affected countries: Bootstrap improvement," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    11. Fu, Xinjie & Wang, JinRong, 2024. "Dynamic behaviors and non-instantaneous impulsive vaccination of an SAIQR model on complex networks," Applied Mathematics and Computation, Elsevier, vol. 465(C).
    12. Mohamed M. Mousa & Fahad Alsharari, 2021. "A Comparative Numerical Study and Stability Analysis for a Fractional-Order SIR Model of Childhood Diseases," Mathematics, MDPI, vol. 9(22), pages 1-12, November.
    13. Mayer Alvo & Jingrui Mu, 2023. "COVID-19 Data Analysis Using Bayesian Models and Nonparametric Geostatistical Models," Mathematics, MDPI, vol. 11(6), pages 1-13, March.
    14. Sharma, Natasha & Verma, Atul Kumar & Gupta, Arvind Kumar, 2021. "Spatial network based model forecasting transmission and control of COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    15. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    16. Pau Fonseca i Casas & Joan Garcia i Subirana & Víctor García i Carrasco & Xavier Pi i Palomés, 2021. "SARS-CoV-2 Spread Forecast Dynamic Model Validation through Digital Twin Approach, Catalonia Case Study," Mathematics, MDPI, vol. 9(14), pages 1-17, July.
    17. Mishra, A.M. & Purohit, S.D. & Owolabi, K.M. & Sharma, Y.D., 2020. "A nonlinear epidemiological model considering asymptotic and quarantine classes for SARS CoV-2 virus," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    18. Khan, Hasib & Ibrahim, Muhammad & Abdel-Aty, Abdel-Haleem & Khashan, M. Motawi & Khan, Farhat Ali & Khan, Aziz, 2021. "A fractional order Covid-19 epidemic model with Mittag-Leffler kernel," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    19. Ghanbari, Behzad, 2021. "On detecting chaos in a prey-predator model with prey’s counter-attack on juvenile predators," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    20. Han, Lili & Song, Sha & Pan, Qiuhui & He, Mingfeng, 2023. "The impact of multiple population-wide testing and social distancing on the transmission of an infectious disease," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(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:gam:jmathe:v:9:y:2021:i:12:p:1321-:d:570981. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.