[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Log in

Global dynamics of a time-fractional spatio-temporal SIR model with a generalized incidence rate

  • Original Research
  • Published:
Journal of Applied Mathematics and Computing Aims and scope Submit manuscript

Abstract

This paper delves into the study of a diffusive SIR epidemic model characterized by reaction–diffusion equations enriched with a fractional derivative within the Caputo framework. Within this model, we incorporate a general incidence function and meticulously analyze how the adoption of mask-wearing and adherence to physical distancing protocols intricately shape the dynamics of susceptible and infected individuals. Our exploration commences by establishing the existence and uniqueness of a positively bounded solution for the model, employing powerful Banach’s fixed point theorem. Moreover, we showcase that this solution demonstrates distinctive global mild attributes. Subsequently, we elucidate the two equilibrium points inherent in the system: the disease-free and endemic points. Employing the LaSalle–Lyapunov theorem, we establish that the global stability of these equilibrium points is predominantly contingent upon the basic reproduction number of the system. This stability assertion holds true across various values of the non-integer order derivative. Lastly, we substantiate our findings with a series of numerical simulations that provide tangible support for the preceding analytical results.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data availibility

All the information and data that were analyzed or generated to support the results of this work are provided within this article.

References

  1. Aguila-Camacho, N., Duarte-Mermoud, M.A., Gallegos, J.A.: Lyapunov functions for fractional order systems. Commun. Nonlinear Sci. Numer. Simul. 19(9), 2951–2957 (2014). https://doi.org/10.1016/j.cnsns.2014.01.022

    Article  MathSciNet  Google Scholar 

  2. Almeida, R.: What is the best fractional derivative to fit data? Appl. Anal. Discrete Math. 11(2), 358–368 (2017)

    Article  MathSciNet  Google Scholar 

  3. Andrade, B.D., Carvalho, A.N., Carvalho-Neto, P.M., Marín-Rubio, P.: Semilinear fractional differential equations: global solutions, critical nonlinearities and comparison results. Topol. Methods. Nonlinear. Anal. (2015). https://doi.org/10.12775/TMNA.2015.022

    Article  MathSciNet  Google Scholar 

  4. Bai, Z., Peng, R., Zhao, X.: A reaction–diffusion malaria model with seasonality and incubation period. J. Math. Biol. 77, 201–228 (2018). https://doi.org/10.1007/s00285-017-1193-7

    Article  MathSciNet  Google Scholar 

  5. Bera, S., Khajanchi, S., Roy, T.K.: Dynamics of an HTLV-I infection model with delayed CTLs immune response. Appl. Math. Comput. 430, 127206 (2022)

    MathSciNet  Google Scholar 

  6. Bera, S., Khajanchi, S., Roy, T.K.: Stability analysis of fuzzy HTLV-I infection model: a dynamic approach. J. Appl. Math. Comput. 69(1), 171–199 (2023)

    Article  MathSciNet  Google Scholar 

  7. Boukhouima, A., Hattaf, K., Lotfi, M., Mahrouf, M., Torres, D.F.M., Yousfi, N.: Lyapunov functions for fractional-order systems in biology: methods and applications. Chaos Solitons Fractals 140, 110224 (2020)

    Article  MathSciNet  Google Scholar 

  8. Bounkaicha, C., Allali, K.: Modelling disease spread with spatio-temporal fractional derivative equations and saturated incidence rate. Model. Earth Syst. Environ. Apr 8:1–13 (2023)

  9. Bounkaicha, C., Allali, K., Tabit, Y., Danane, J.: Global dynamic of spatio-temporal fractional order SEIR model. Math. Model. Comput. 10(2), 299–310 (2023)

    Article  Google Scholar 

  10. Cai, L.-M., Li, X.-Z.: Analysis of a SEIV epidemic model with a nonlinear incidence rate. Appl. Math. Model. 33(7), 2919–2926 (2009)

    Article  MathSciNet  Google Scholar 

  11. Djebara, L., Abdelmalek, S., Bendoukha, S.: Asymptotic stability of an epidemiological fractional reaction–diffusion model. Demonstratio Mathematica (2023). https://doi.org/10.1515/dema-2022-0224

    Article  MathSciNet  Google Scholar 

  12. Diethelm, K.: A fractional calculus based model for the simulation of an outbreak of dengue fever. Nonlinear Dyn. 71(1), 613–619 (2013). https://doi.org/10.1007/s11071-012-0475-2

    Article  MathSciNet  Google Scholar 

  13. Dwivedi, A., Keval, R., Khajanchi, S.: Modeling optimal vaccination strategy for dengue epidemic model: a case study of India. Physica Scripta 97(8), 085214 (2022)

    Article  Google Scholar 

  14. Fatoorehchi, H., Abolghasemi, H., Zarghami, R., Rach, R.: Feedback control strategies for a cerium-catalyzed Belousov–Zhabotinsky chemical reaction system. Can. J. Chem. Eng. 93(7), 1212–1221 (2015)

    Article  Google Scholar 

  15. Fatoorehchi, H., Alidadi, M., Rach, R., Shojaeian, A.: Theoretical and experimental investigation of thermal dynamics of Steinhart–Hart negative temperature coefficient thermistors. J. Heat Transf. 141(7), 072003 (2019)

    Article  Google Scholar 

  16. Hattaf, K., Yousfi, N: Global stability for fractional diffusion equations in biological systems. Comple. 2020, 6

  17. Kucharski, A.J., Russell, T.W., Diamond, C., Liu, Y., Edmunds, J., Funk, S., Eggo, R.M.: Early dynamics of transmission and control of COVID-19: a mathematical modelling study. Articles Lancet Infect Dis. 20, 553–58 (2020). https://doi.org/10.1016/S1473-3099(20)30144-4

    Article  Google Scholar 

  18. Kumar Rai, R., Kumar Tiwari, P., Khajanchi, S.: Modeling the influence of vaccination coverage on the dynamics of COVID-19 pandemic with the effect of environmental contamination. Math. Methods Appl. Sci. 46(12), 12425–12453 (2023)

    Article  MathSciNet  Google Scholar 

  19. Kyrychko, Y. N., Blyuss, K. B.: Global properties of a delayed SIR model with temporary immunity and nonlinear incidence rate. Nonlinear analysis: real world applications. 6(3), (2005)

  20. Lin, Y., Xu, C.: Finite difference/spectral approximations for the time-fractional diffusion equation. J. Comput. Phys. 225(2), 1533–1552 (2007)

    Article  MathSciNet  Google Scholar 

  21. Lu, Z., Yu, Y., Ren, G., Xu, C., Meng, X.: Global dynamics for a class of reaction-diffusion multigroup SIR epidemic models with time fractional-order derivatives. Nonlinear Anal-Model. 27(1), 142–162 (2022). https://doi.org/10.15388/namc.2022.27.25192

  22. Majee, S., Adak, S., Jana, S., et al.: Complex dynamics of a fractional-order SIR system in the context of COVID-19. J. Appl. Math. Comput. 68, 4051–4074 (2022). https://doi.org/10.1007/s12190-021-01681-z

    Article  MathSciNet  Google Scholar 

  23. Mondal, J., Khajanchi, S., Samui, P.: Impact of media awareness in mitigating the spread of an infectious disease with application to optimal control. The European Physical Journal Plus. 137(8), (2022)

  24. Moussaoui, A., Zerga, E.: Transmission dynamics of COVID-19 in Algeria: The impact of physical distancing and face masks. AIMS Public Health. 7(4), 816–827 (2020)

    Article  Google Scholar 

  25. Podlubny, I.: Fractional differential equations; Math. Sci. Eng. 198, Academic Press, Inc. San Diego, CA (1999)

  26. Ray, S. S., Bera, R. K.: An approximate solution of a nonlinear fractional differential equation by Adomian decomposition method. Applied Mathematics and Computation. 167(1), (2005)

  27. Ren, X., Tian, Y., Liu L., Liu., X.: A reaction–diffusion within-host HIV model with cell-to-cell transmission. J. Math. Biol. 76(7), 1831–1872 (2018)

  28. Saeedian, M., Khalighi, M., Azimi-Tafreshi, N., Jafari, G. R., Ausloos, M.: Memory effects on epidemic evolution: The susceptible-infected-removed epidemic model. Phys. Rev. E. 95(2) (2017)

  29. Sarkar, K., Khajanchi, S.: Spatiotemporal dynamics of a predator–prey system with fear effect. J. Frankl. Inst. 360(11), 7380–7414 (2023)

  30. Sarkar, K., Mondal, J., Khajanchi, S.: How do the contaminated environment influence the transmission dynamics of COVID-19 pandemic? The European Physical Journal Special Topics. 231, (2022)

  31. Shu, X.-B., Xu, F.: The existence of solutions for impulsive fractional partial neutral differential equations. J. Math. (2013). https://doi.org/10.1155/2013/147193

    Article  MathSciNet  Google Scholar 

  32. Sidi Ammi, M.R., Tahiri, M., Tilioua, M., Zeb, A., Khan, I., Andualem, M.: Global Analysis of a time fractional order spatio-temporal SIR model. Scientific Reports (2022). https://doi.org/10.1038/s41598-022-08992-6

    Article  Google Scholar 

  33. Sidi Ammi, M.R., Tahiri, M., Torres, D.F.M.: Global stability of a Caputo fractional SIRS model with general incidence rate. Math. Comput. Sci. (2020). https://doi.org/10.1007/s11786-020-00467-z

    Article  Google Scholar 

  34. Siettos, C. I., Russo, L.: Mathematical modeling of infectious disease dynamics. Virulence 4:4, 295-306 (2013) https://doi.org/10.4161/viru.24041

  35. Silver, S.D., van den Driessche, P. Khajanchi, S.: A dynamic multistate and control model of the COVID-19 pandemic. J Public Health (Berl.) (2023). https://doi.org/10.1007/s10389-023-02014-z

  36. Smith, H.L.: Monotone Dynamical Systems: An Introduction to the Theory of Competitive and Cooperative Systems. J. Am. Math, Soc (1995)

    Google Scholar 

  37. Swati, N.: Fractional order SIR epidemic model with Beddington-De Angelis incidence and Holling type II treatment rate for COVID-19. J. Appl. Math. Comput. 68, 3835–3859 (2022). https://doi.org/10.1007/s12190-021-01658-y

    Article  MathSciNet  Google Scholar 

  38. Vales, E.A., Pérez, Á.G.C.: Dynamics of a reaction-diffusion SIRS model with general incidence rate in a heterogeneous environment. Z. fur Angew. Math. Phys. 73(1), 9 (2022). https://doi.org/10.1007/s00033-021-01645-0

    Article  MathSciNet  Google Scholar 

  39. Van den Driessche, P., Watmough, J.: Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Math. Biosci. 180, 29–48 (2002)

    Article  MathSciNet  Google Scholar 

  40. Wang, J., Gao, S., Li, X., et al.: A TB Model with Infectivity in Latent Period and Imperfect Treatment, Discrete Dynamics in Nature and Society. 2012, (2012) https://doi.org/10.1155/2012/184918

  41. Zhu, H. , Wei L., Niu, P.: The novel coronavirus outbreak in Wuhan, China. Global Health Research and Policy. 5, (2020) https://doi.org/10.1186/s41256-020-00135-6

Download references

Acknowledgements

The authors wish to extend their deepest appreciation to the editor and the anonymous reviewers for their remarkable dedication and invaluable feedback, which greatly improved the paper’s quality.

Funding

The authors assert that no funding was received for the preparation and execution of this manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ayoub Bouissa.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bouissa, A., Tahiri, M., Tsouli, N. et al. Global dynamics of a time-fractional spatio-temporal SIR model with a generalized incidence rate. J. Appl. Math. Comput. 69, 4779–4804 (2023). https://doi.org/10.1007/s12190-023-01932-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12190-023-01932-1

Keywords

Mathematics Subject Classification

Navigation