Skip to main content
Log in

Spatio-temporal dynamics of an SIS model with nonlinear incidence and nonlocal disease transmission

  • Original Paper
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

Investigation of the spatio-temporal patterns exhibited by infected communities sharing the same spatial region is the focus of many researchers. Typically, an individual’s susceptibility is substantially connected with the distance from nearby affected persons. Such a disease propagation mechanism is called the nonlocal infection which is primarily modeled with a kernel function K, whose support determines the range of the nonlocal infection area. In our current study, a susceptible–infected–susceptible-type epidemic model is analyzed considering the nonlinear disease incidence rate which is further extended to incorporate the nonlocal disease transmission and random movement of the individuals. Complete bifurcation characteristics of the associated temporal model include the saddle-node, subcritical Hopf, and homoclinic bifurcations. Our primary emphasis is to investigate the formation of a wide variety of spatio-temporal patterns that include stationary, quasi-periodic, periodic, and chaotic patterns, among others. Comparisons have been made between the spatio-temporal dynamics of the local and nonlocal disease transmission models. It is observed that the nonlocal disease transmission expands the parametric domain (referred to as Hopf and stable domains) on which the system possesses oscillatory and spatially homogeneous solutions. As a result, the spatially heterogeneous stationary solutions (referred to as Turing patterns) of the local system turn into irregular oscillatory solutions or spatially homogeneous solutions whenever the nonlocal extent of the disease transmission gradually increases. Also, the increased range of nonlocal infections reduces the number of stationary patches. In addition, the system exhibits “long transient” dynamics when the dispersal rate of the population tends to the Turing threshold. Exhaustive numerical simulations have been carried out to illustrate the wide range of spatio-temporal patterns displayed by the system in the presence and absence of nonlocal terms.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

Data availability

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study. However, the codes or algorithms used in the simulation will be made available on specific requests.

References

  1. Kermack, W.O., McKendrick, A.G.: A contribution to the mathematical theory of epidemics. Proc. Roy. Soc. Lond. Ser. A Contain. Pap. Math. Phys. Charact. 115(772), 700–721 (1927)

    MATH  Google Scholar 

  2. Ghosh, S., Volpert, V., Banerjee, M.: An epidemic model with time-distributed recovery and death rates. Bull. Math. Biol. 84(8), 78 (2022)

    MathSciNet  MATH  Google Scholar 

  3. Das, D.K., Kar, T.: Global dynamics of a tuberculosis model with sensitivity of the smear microscopy. Chaos Solitons Fractals 146, 110879 (2021)

    MathSciNet  Google Scholar 

  4. d’Onofrio, A.: A note on the global behaviour of the network-based sis epidemic model. Nonlinear Anal. Real World Appl. 9(4), 1567–1572 (2008)

    MathSciNet  MATH  Google Scholar 

  5. Keeling, M.J., Rohani, P.: Modeling Infectious Diseases in Humans and Animals. Princeton University Press (2008)

    MATH  Google Scholar 

  6. Wang, Z., Bauch, C.T., Bhattacharyya, S., d’Onofrio, A., Manfredi, P., Perc, M., Perra, N., Salathé, M., Zhao, D.: Statistical physics of vaccination. Phys. Rep. 664, 1–113 (2016)

    MathSciNet  MATH  Google Scholar 

  7. Li, H.-J., Xu, W., Song, S., Wang, W.-X., Perc, M.: The dynamics of epidemic spreading on signed networks. Chaos Solitons Fractals 151, 111294 (2021)

    MathSciNet  MATH  Google Scholar 

  8. d’Onofrio, A., Manfredi, P.: Behavioral sir models with incidence-based social-distancing. Chaos Solitons Fractals 159, 112072 (2022)

    MathSciNet  Google Scholar 

  9. Jana, S., Nandi, S.K., Kar, T.: Complex dynamics of an sir epidemic model with saturated incidence rate and treatment. Acta. Biotheor. 64(1), 65–84 (2016)

    Google Scholar 

  10. Van den Driessche, P., Watmough, J.: Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Math. Biosci. 180(1–2), 29–48 (2002)

    MathSciNet  MATH  Google Scholar 

  11. Ruan, S., Wang, W.: Dynamical behavior of an epidemic model with a nonlinear incidence rate. J. Differ. Equ. 188(1), 135–163 (2003)

    MathSciNet  MATH  Google Scholar 

  12. Banerjee, M., Volpert, V.: Spatio-temporal pattern formation in Rosenzweig–Macarthur model: effect of nonlocal interactions. Ecol. Complex. 30, 2–10 (2017)

    Google Scholar 

  13. Malchow, H., Hilker, F.M., Siekmann, I., Petrovskii, S.V., Medvinsky, A.B.: Mathematical models of pattern formation in planktonic predation–diffusion systems: a review. Aspects Math. Modell. 8, 1–26 (2008)

    MathSciNet  MATH  Google Scholar 

  14. Dey, S., Banerjee, M., Ghorai, S.: Analytical detection of stationary turing pattern in a predator–prey system with generalist predator. Math. Modell. Nat. Phenom. 17, 33 (2022)

    MathSciNet  MATH  Google Scholar 

  15. Paquin-Lefebvre, F., Nagata, W., Ward, M.J.: Pattern formation and oscillatory dynamics in a two-dimensional coupled bulk-surface reaction–diffusion system. SIAM J. Appl. Dyn. Syst. 18(3), 1334–1390 (2019)

    MathSciNet  MATH  Google Scholar 

  16. Zhang, L., Liu, J., Banerjee, M.: Hopf and steady state bifurcation analysis in a ratio-dependent predator–prey model. Commun. Nonlinear Sci. Numer. Simul. 44, 52–73 (2017)

    MathSciNet  MATH  Google Scholar 

  17. Murray, J.D.: Mathematical Biology II: Spatial Models and Biomedical Applications, vol. 3. Springer (2001)

    Google Scholar 

  18. Raffel, T.R., Martin, L.B., Rohr, J.R.: Parasites as predators: unifying natural enemy ecology. Trends Ecol. Evol. 23(11), 610–618 (2008)

    Google Scholar 

  19. Malchow, H., Petrovskii, S., Venturino, E.: Spatiotemporal Patterns in Ecology and Epidemiology: Theory, Models, and Simulation. Chapman and Hall/CRC (2008)

    MATH  Google Scholar 

  20. González, E., Villena, M.J.: On the spatial dynamics of vaccination: a spatial sirs-v model. Comput. Math. Appl. 80(5), 733–743 (2020)

    MathSciNet  MATH  Google Scholar 

  21. Allen, L.J., Bolker, B.M., Lou, Y., Nevai, A.L.: Asymptotic profiles of the steady states for an sis epidemic reaction–diffusion model. Discrete Contin. Dyn. Syst. 21(1), 1 (2008)

    MathSciNet  MATH  Google Scholar 

  22. Sun, G.-Q., Jusup, M., Jin, Z., Wang, Y., Wang, Z.: Pattern transitions in spatial epidemics: mechanisms and emergent properties. Phys. Life Rev. 19, 43–73 (2016)

    Google Scholar 

  23. Li, L.: Patch invasion in a spatial epidemic model. Appl. Math. Comput. 258, 342–349 (2015)

    MathSciNet  MATH  Google Scholar 

  24. Zhang, G.-B., Li, Y., Feng, Z.: Exponential stability of traveling waves in a nonlocal dispersal epidemic model with delay. J. Comput. Appl. Math. 344, 47–72 (2018)

    MathSciNet  MATH  Google Scholar 

  25. Tian, B., Yuan, R.: Traveling waves for a diffusive seir epidemic model with non-local reaction. Appl. Math. Model. 50, 432–449 (2017)

    MathSciNet  MATH  Google Scholar 

  26. Maidana, N.A., Yang, H.M.: Spatial spreading of West Nile Virus described by traveling waves. J. Theor. Biol. 258(3), 403–417 (2009)

    MathSciNet  MATH  Google Scholar 

  27. Adimy, M., Chekroun, A., Kazmierczak, B.: Traveling waves for reaction–diffusion PDE coupled to difference equation with nonlocal dispersal term and time delay. Math. Model. Nat. Phenom. 17, 17 (2022)

    MathSciNet  MATH  Google Scholar 

  28. Liu, Z., Shen, Z., Wang, H., Jin, Z.: Analysis of a local diffusive sir model with seasonality and nonlocal incidence of infection. SIAM J. Appl. Math. 79(6), 2218–2241 (2019)

    MathSciNet  MATH  Google Scholar 

  29. Liu, W.-M., Levin, S.A., Iwasa, Y.: Influence of nonlinear incidence rates upon the behavior of sirs epidemiological models. J. Math. Biol. 23(2), 187–204 (1986)

    MathSciNet  MATH  Google Scholar 

  30. Liu, W.-M., Hethcote, H.W., Levin, S.A.: Dynamical behavior of epidemiological models with nonlinear incidence rates. J. Math. Biol. 25(4), 359–380 (1987)

    MathSciNet  MATH  Google Scholar 

  31. Pal, S., Ghorai, S., Banerjee, M.: Analysis of a prey–predator model with non-local interaction in the prey population. Bull. Math. Biol. 80(4), 906–925 (2018)

    MathSciNet  MATH  Google Scholar 

  32. Pal, S., Ghorai, S., Banerjee, M.: Effect of kernels on spatio-temporal patterns of a non-local prey–predator model. Math. Biosci. 310, 96–107 (2019)

    MathSciNet  MATH  Google Scholar 

  33. Manna, K., Volpert, V., Banerjee, M.: Pattern formation in a three-species cyclic competition model. Bull. Math. Biol. 83(5), 1–35 (2021)

    MathSciNet  MATH  Google Scholar 

  34. Banerjee, M., Volpert, V.: Prey-predator model with a nonlocal consumption of prey. Chaos Interdiscip. J. Nonlinear Sci. 26(8), 083120 (2016)

    MathSciNet  MATH  Google Scholar 

  35. Manna, K., Volpert, V., Banerjee, M.: Dynamics of a diffusive two-prey-one-predator model with nonlocal intra-specific competition for both the prey species. Mathematics 8(1), 101 (2020)

    Google Scholar 

  36. Manna, K., Banerjee, M.: Spatiotemporal pattern formation in a prey–predator model with generalist predator. Math. Modell. Nat. Phenom. 17, 6 (2022)

    MathSciNet  MATH  Google Scholar 

  37. Autry, E.A., Bayliss, A., Volpert, V.A.: Biological control with nonlocal interactions. Math. Biosci. 301, 129–146 (2018)

    MathSciNet  MATH  Google Scholar 

  38. Wang, T.: Dynamics of an epidemic model with spatial diffusion. Physica A 409, 119–129 (2014)

  39. Sun, G.-Q., Jin, Z., Liu, Q.-X., Li, L.: Chaos induced by breakup of waves in a spatial epidemic model with nonlinear incidence rate. J. Stat. Mech. Theory Exp. 2008(08), 08011 (2008)

    Google Scholar 

  40. Hastings, A., Higgins, K.: Persistence of transients in spatially structured ecological models. Science 263(5150), 1133–1136 (1994)

  41. Hastings, A., Abbott, K.C., Cuddington, K., Francis, T., Gellner, G., Lai, Y.-C., Morozov, A., Petrovskii, S., Scranton, K., Zeeman, M.L.: Transient phenomena in ecology. Science 361(6406), 6412 (2018)

    Google Scholar 

  42. Morozov, A., Abbott, K., Cuddington, K., Francis, T., Gellner, G., Hastings, A., Lai, Y.-C., Petrovskii, S., Scranton, K., Zeeman, M.L.: Long transients in ecology: theory and applications. Phys. Life Rev. 32, 1–40 (2020)

    Google Scholar 

  43. Tao, Y., Hite, J.L., Lafferty, K.D., Earn, D.J., Bharti, N.: Transient disease dynamics across ecological scales. Thyroid Res. 14(4), 625–640 (2021)

    Google Scholar 

  44. Hethcote, H.W., van den Driessche, P.: Some epidemiological models with nonlinear incidence. J. Math. Biol. 29(3), 271–287 (1991)

    MathSciNet  MATH  Google Scholar 

  45. Moghadas, S.M., Gumel, A.B.: Global stability of a two-stage epidemic model with generalized non-linear incidence. Math. Comput. Simul. 60(1–2), 107–118 (2002)

    MathSciNet  MATH  Google Scholar 

  46. Bauch, C.T., Earn, D.J.: Transients and attractors in epidemics. Proc. Roy. Soc. Lond. Ser B Biol. Sci. 270(1524), 1573–1578 (2003)

    Google Scholar 

Download references

Acknowledgements

The author Dhiraj Kumar Das gratefully acknowledges the financial support provided by the Science and Engineering Research Board, Government of India, through the National Postdoctoral Fellowship scheme under the file number PDF/2021/001915, dated January 4, 2022.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dhiraj Kumar Das.

Ethics declarations

Conflict of interest

The authors state here that they have no known competing financial interests or personal relationships that could have appeared to influence the work accounted for in this paper.

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

Das, D.K., Ghorai, S. & Banerjee, M. Spatio-temporal dynamics of an SIS model with nonlinear incidence and nonlocal disease transmission. Nonlinear Dyn 111, 15591–15612 (2023). https://doi.org/10.1007/s11071-023-08633-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-023-08633-1

Keywords

Navigation