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Analysis of a fuzzy epidemic model with saturated treatment and disease transmission

    https://doi.org/10.1142/S179352451850002XCited by:8 (Source: Crossref)

    In this paper, we describe an SIS epidemic model where both the disease transmission rate and treatment function are considered in saturated forms. The dynamical behavior of the system is analyzed. The system is customized by considering the disease transmission rate and treatment control as fuzzy numbers and then fuzzy expected value of the infected individuals is determined. The fuzzy basic reproduction number is investigated and a threshold condition of pathogen is derived at which the system undergoes a backward bifurcation.

    AMSC: 92D30, 34A07

    References

    • 1. W. O. Kermack and A. G. Mackendric, Contribution to the mathematical theory of epidemics, Proc. Roy. Soc. London Ser. A 115 (1927) 700–721. Google Scholar
    • 2. T. K. Kar and S. Jana, A theoretical study on mathematical modelling of an infectious disease with application of optimal control, Biosystems 111 (2013) 37–50. ISIGoogle Scholar
    • 3. J. C. Eckalbar and W. L. Eckalbar, Dynamics of an epidemic model with quadratic treatment, Nonlinear Anal. Real World Appl. 12(1) (2011) 320–332. ISIGoogle Scholar
    • 4. T. K. Kar and P. K. Mandal, Global dynamics of a tuberculosis epidemic model and the influence of backward bifurcation, J. Math. Model. Algorithm 11 (2012) 433–459. Google Scholar
    • 5. A. B. Gumel and S. M. Moghadas, A qualitative study of a vaccination model with nonlinear incidence, Appl. Math. Comput. 143 (2003) 409–419. ISIGoogle Scholar
    • 6. B. Buonomo and D. Lacitignola, On the backward bifurcation of a vaccination model with nonlinear incidence, Nonlinear Anal. Model. Control 16(1) (2008) 30–46. ISIGoogle Scholar
    • 7. Y. Zhou, K. Yang, K. Zhou and Y. Liang, Optimal vaccination policies for an SIR model with limited resources, Acta Biotheor. 62 (2014) 171–181. ISIGoogle Scholar
    • 8. J. D. Murray, Mathematical Biology (Springer, Berlin, 2002). Google Scholar
    • 9. T. K. Kar, S. Jana and A. Ghorai, Effect of isolation in an infectious disease, Int. J. Ecol. Econ. Statist. 29(2) (2013) 87–106. Google Scholar
    • 10. T. K. Kar and S. Jana, Application of three controls optimally in a vector-borne disease — A mathematical study, Commun. Nonlinear Sci. Numer. Simulat. 18 (2013) 2868–2884. ISIGoogle Scholar
    • 11. D. H. Thomasey and M. Martcheva, Serotype replacement of vertically transmitted disease through perfect vaccination, J. Biol. Syst. 16(2) (2008) 255–277. Link, ISIGoogle Scholar
    • 12. J. Arino, K. L. Cooke, P. van den Driessche and J. Velasco-Hernandez, An epidemiology model that includes a leaky vaccine with a general waning function, Dynam. Syst. Ser. B 4(2) (2004) 479–495. ISIGoogle Scholar
    • 13. O. D. Makinde, Adomian decomposition approach to a SIR epidemic model with constant vaccination strategy, Appl. Math. Comput. 184 (2007) 842–848. ISIGoogle Scholar
    • 14. Z. Qiu and Z. Feng, Transmission dynamics of an influenza model with vaccination and antiviral treatment, Bull. Math. Biol. 72(1) (2010) 1–33. ISIGoogle Scholar
    • 15. Z. Hu, W. Ma and S. Ruan, Analysis of SIR epidemic models with nonlinear incidence rate and treatment, Math. Biosci. 238(1) (2012) 12–20. ISIGoogle Scholar
    • 16. L. Zhou and M. Fan, Dynamics of an SIR epidemic model with limited resources visited, Nonlinear Anal. Real World Appl. 13 (2012) 312–324. ISIGoogle Scholar
    • 17. K. Okosun, R. Ouifki and N. Marcus, Optimal control analysis of a malaria disease transmission model that includes treatment and vaccination with waning immunity, Biosystems 106 (2011) 136–145. ISIGoogle Scholar
    • 18. H. Laarabi, A. Abta and K. Hattaf, Optimal control of a delayed SIRS epidemic model with vaccination and treatment, Acta Biotheor. 63(2) (2015) 87–97, Doi: https://doi.org/10.1007/s10441-015-9244-1 ISIGoogle Scholar
    • 19. F. Brauer, Backward bifurcation in simple vaccination treatment models, J. Biol. Dynam. 5(5) (2011) 1–28. Google Scholar
    • 20. V. Capasso and G. Serio, A generalization of the Kermack–Mackendric deterministic epidemic model, Math. Biosci. 42 (1978) 43–61. ISIGoogle Scholar
    • 21. X. Zhang and X. Liu, Bifurcation of an epidemic model with saturated treatment, J. Math. Anal. Appl. 348 (2008) 433–443. ISIGoogle Scholar
    • 22. S. Jana, S. K. Nandi and T. K. Tar, Complex dynamics of an SIR epidemic model with saturated incidence rate and treatment, Acta Biotheor. 64 (2016) 65–84. ISIGoogle Scholar
    • 23. L. A. Zadeh, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets Syst. 1 (1978) 3–28. Google Scholar
    • 24. O. A. Arqub and A. El-Ajou, Solution of the fractional epidemic model by homotophy analysis method, J. King Saud Univ. (Sci.) 25 (2013) 73–81. Google Scholar
    • 25. O. A. Arqub, A. El-Ajou, S. Momani and N. Shawagfeh, Analytical solutions of fuzzy initial value problem by HAM, Appl. Math. Inform. Sci. 7 (2013) 1903–1919. ISIGoogle Scholar
    • 26. O. A. Arqub, Series solution of a fuzzy differential equation under strongly generalized differentiability, J. Adv. Res. Appl. Math. 5 (2013) 31–52. Google Scholar
    • 27. R. Jafelice, L. C. Barros, R. C. Bassanezei and F. Gomide, Fuzzy modeling in symptomatic HIV virus infected population, Bull. Math. Biol. 66 (2004) 1597–1620. ISIGoogle Scholar
    • 28. E. Massad, N. R. S. Ortega, L. C. D. Barros and C. S. Struchiner, Fuzzy Logic in Action: Application of Epidemiology and Beyond (Springer, 2008). Google Scholar
    • 29. B. K. Mishra and M. K. Pandey, Fuzzy epidemic model for the transmission of worms in a computer network, Nonlinear Anal. 11 (2010) 4435–4341. Google Scholar
    • 30. M. Sugeno, Theory of fuzzy integrals and its applications, Ph.D. Thesis (Tokyo Institute of Technology, 1974). Google Scholar
    • 31. P. K. Mondal, S. Jana, P. Haldar and T. K. Kar, Dynamical behavior of an epidemic model in a fuzzy transmission, Int. J. Unc. Fuzz. Knowl. Based Syst. 23(5) (2015) 651–665. Link, ISIGoogle Scholar
    • 32. S. Jana, P. Haldar and T. K. Kar, Optimal control and stability analysis of an epidemic model with population dispersal, Chaos, Solitons Fractals 83 (2016) 67–81. ISIGoogle Scholar