Research article

A study on the transmission and dynamical behavior of an HIV/AIDS epidemic model with a cure rate

  • Received: 27 May 2022 Revised: 25 June 2022 Accepted: 30 June 2022 Published: 29 July 2022
  • MSC : 34A12, 34K28

  • In developing nations, the human immunodeficiency virus (HIV) infection, which can lead to acquired immunodeficiency syndrome (AIDS), has become a serious infectious disease. It destroys millions of people and costs incredible amounts of money to treat and control epidemics. In this research, we implemented a Legendre wavelet collocation scheme for the model of HIV infection and compared the new findings to previous findings in the literature. The findings demonstrate the precision and practicality of the suggested approach for approximating the solutions of HIV model. Additionally, establish an autonomous non-linear model for the transmission dynamics of healthy CD4+ T-cells, infected CD4+ T-cells and free particles HIV with a cure rate. Through increased human immunity, the cure rate contributes to a reduction in infected cells and viruses. Using the Routh-Hurwitz criterion, we determine the basic reproductive number and assess the stability of the disease-free equilibrium and unique endemic equilibrium of the model. Furthermore, numerical simulations of the novel model are presented using the suggested approach to demonstrate the efficiency of the key findings.

    Citation: Attaullah, Sultan Alyobi, Mansour F. Yassen. A study on the transmission and dynamical behavior of an HIV/AIDS epidemic model with a cure rate[J]. AIMS Mathematics, 2022, 7(9): 17507-17528. doi: 10.3934/math.2022965

    Related Papers:

  • In developing nations, the human immunodeficiency virus (HIV) infection, which can lead to acquired immunodeficiency syndrome (AIDS), has become a serious infectious disease. It destroys millions of people and costs incredible amounts of money to treat and control epidemics. In this research, we implemented a Legendre wavelet collocation scheme for the model of HIV infection and compared the new findings to previous findings in the literature. The findings demonstrate the precision and practicality of the suggested approach for approximating the solutions of HIV model. Additionally, establish an autonomous non-linear model for the transmission dynamics of healthy CD4+ T-cells, infected CD4+ T-cells and free particles HIV with a cure rate. Through increased human immunity, the cure rate contributes to a reduction in infected cells and viruses. Using the Routh-Hurwitz criterion, we determine the basic reproductive number and assess the stability of the disease-free equilibrium and unique endemic equilibrium of the model. Furthermore, numerical simulations of the novel model are presented using the suggested approach to demonstrate the efficiency of the key findings.



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    [1] J. M. Hyman, J. Li, E. A. Stanley, The differential infectivity and staged progression models for the transmission of HIV, Math. Biosci., 155 (1999), 77–109. https://doi.org/10.1016/S0025-5564(98)10057-3 doi: 10.1016/S0025-5564(98)10057-3
    [2] X. D. Lin, H. W. Hethcote, P. Van den Driessche, An epidemiological model for HIV/AIDS with proportional recruitment, Math. Biosci., 118 (1993), 181–195. https://doi.org/10.1016/0025-5564(93)90051-B doi: 10.1016/0025-5564(93)90051-B
    [3] C. C. McCluskey, A model of HIV/AIDS with staged progression and amelioration, Math. Biosci., 181 (2003), 1–16. https://doi.org/10.1016/S0025-5564(02)00149-9 doi: 10.1016/S0025-5564(02)00149-9
    [4] T. Bastys, V. Gapsys, N. T. Doncheva, R. Kaiser, B. L. de Groot, O. V. Kalinina, Consistent prediction of mutation effect on drug binding in HIV-1 protease using alchemical calculations, J. Chem. Theory Comput., 14 (2018), 3397–3408. https://doi.org/10.1021/acs.jctc.7b01109 doi: 10.1021/acs.jctc.7b01109
    [5] H. B. Guo, Y. L. Michael, Global dynamics of a staged-progression model for HIV/AIDS with amelioration, Nonlinear Anal.-Real, 12 (2011), 2529–2540. https://doi.org/10.1016/j.nonrwa.2011.02.021 doi: 10.1016/j.nonrwa.2011.02.021
    [6] M. E. Schechter, B. B. Andrade, T. Y. He, G. H. Richter, K.W. Tosh, B. B. Policicchio, et al., Inflammatory monocytes expressing tissue factor drive SIV and HIV-coagulopathy, Sci. Transl. Med., 9 (2017), eaam5441. https://doi.org/10.1126/scitranslmed.aam5441
    [7] A. Yusuf, U. T. Mustapha, T. A. Sulaiman, E. Hincal, M. Bayram, Modeling the effect of horizontal and vertical transmissions of HIV infection with Caputo fractional derivative, Chaos Soliton. Fract., 145 (2021), 110794. https://doi.org/10.1016/j.chaos.2021.110794 doi: 10.1016/j.chaos.2021.110794
    [8] H. Singh, Analysis of drug treatment of the fractional HIV infection model of CD4+ T-cells, Chaos Soliton. Fract., 146 (2021), 110868. https://doi.org/10.1016/j.chaos.2021.110868 doi: 10.1016/j.chaos.2021.110868
    [9] S. Thirumalai, R. Seshadri, S. Yuzbasi, Spectral solutions of fractional differential equations modeling combined drug therapy for HIV infection, Chaos Soliton. Fract., 151 (2021), 111234. https://doi.org/10.1016/j.chaos.2021.111234 doi: 10.1016/j.chaos.2021.111234
    [10] N. H. Al Shamrani, Stability of a general adaptive immunity HIV infection model with silent infected cell-to-cell spread, Chaos Soliton. Fract., 150 (2021), 110422. https://doi.org/10.1016/j.chaos.2020.110422 doi: 10.1016/j.chaos.2020.110422
    [11] Fatmawati, M.A. Khan, H. P. Odinsyah, Fractional model of HIV transmission with awareness effect, Chaos Soliton. Fract., 138 (2020), 109967. https://doi.org/10.1016/j.chaos.2020.109967 doi: 10.1016/j.chaos.2020.109967
    [12] A. H. Abdel-Aty, M. M. A. Khater, H. Dutta, J. Bouslimi, M. Omri, Computational solutions of the HIV-1 infection of CD4+ T-cells fractional mathematical model that causes acquired immunodeficiency syndrome (AIDS) with the effect of antiviral drug therapy, Chaos Soliton. Fract., 139 (2020), 110092. https://doi.org/10.1016/j.chaos.2020.110092 doi: 10.1016/j.chaos.2020.110092
    [13] A. Singh, B. Razooky, C. D. Cox, M. L. Simpson, L. S. Weinberger, Transcriptional bursting from the HIV-1 promoter is a significant source of stochastic noise in HIV-1 gene expression, Biophys. J., 98 (2010), L32–L34. https://doi.org/10.1016/j.bpj.2010.03.001 doi: 10.1016/j.bpj.2010.03.001
    [14] X. R. Mao, G. Marion, E. Renshaw, Environmental Brownian noise suppresses explosions in population dynamics, Stoch. Proc. Appl., 97(2002), 95–110. https://doi.org/10.1016/S0304-4149(01)00126-0 doi: 10.1016/S0304-4149(01)00126-0
    [15] O. M. Ogunlaran, S. C. O. Noutchie, Mathematical model for an effective management of HIV infection, BioMed Res. Int., 2016 (2016), 4217548. https://doi.org/10.1155/2016/4217548 doi: 10.1155/2016/4217548
    [16] R. P. Duffin, R. H. Tullis, Mathematical models of the complete course of HIV infection and AIDS, Comput. Math. Method. M., 4(2002), 826239. https://doi.org/10.1080/1027366021000051772 doi: 10.1080/1027366021000051772
    [17] E. O. Omondi, R. W. Mbogo, L. S. Luboobi, Mathematical modelling of the impact of testing, treatment and control of HIV transmission in Kenya, Cogent Math. Stat., 5 (2018), 1475590. https://doi.org/10.1080/25742558.2018.1475590 doi: 10.1080/25742558.2018.1475590
    [18] D. Wodarz, M. A. Nowak, Mathematical models of HIV pathogenesis and treatment, Bio. Essays, 24 (2002), 1178–1187. https://doi.org/10.1002/bies.10196 doi: 10.1002/bies.10196
    [19] A. Ida, S. Oharu, Y. Oharu, A mathematical approach to HIV infection dynamics, J. Comput. Appl. Math., 204 (2007), 172–186. https://doi.org/10.1016/j.cam.2006.04.057 doi: 10.1016/j.cam.2006.04.057
    [20] A. Mastroberardino, Y. J. Cheng, A. Abdelrazec, H. Liu, Mathematical modeling of the HIV/AIDS epidemic in Cuba, Int. J. Biomath., 8 (2015), 1550047. https://doi.org/10.1142/S1793524515500473 doi: 10.1142/S1793524515500473
    [21] Attaullah, M. Sohaib, Mathematical modeling and numerical simulation of HIV infection model, Res. Appl. Math., 7 (2020), 100118. https://doi.org/10.1016/j.rinam.2020.100118 doi: 10.1016/j.rinam.2020.100118
    [22] K. Theys, P. Libin, A. C. Pineda-Pena, A. Nowe, A. M. Vandamme, A. B. Abecasis, The impact of HIV-1 within-host evolution on transmission dynamics, Curr. Opin. Virol., 28 (2018), 92–101. https://doi.org/10.1016/j.coviro.2017.12.001 doi: 10.1016/j.coviro.2017.12.001
    [23] F. Bozkurt, F. Peker, Mathematical modelling of HIV epidemic and stability analysis, Adv. Differ. Equ., 2014 (2014), 95. https://doi.org/10.1186/1687-1847-2014-95 doi: 10.1186/1687-1847-2014-95
    [24] E. A. Nosova, A. A. Romanyukha, Mathematical model of HIV-infection transmission and dynamics in the size of risk groups, Math. Models Comput. Simul., 5 (2013), 379–393. https://doi.org/10.1134/S207004821304011X doi: 10.1134/S207004821304011X
    [25] X. D. Sun, H. Nishiura, Y. N. Xiao, Modeling methods for estimating HIV incidence: A mathematical review, Theor. Biol. Med. Model., 17 (2020), 1. https://doi.org/10.1186/s12976-019-0118-0 doi: 10.1186/s12976-019-0118-0
    [26] N. H. Sweilam, S. M. AL-Mekhlafi, Z. N. Mohammed, D. Baleanu, Optimal control for variable order fractional HIV/AIDS and malaria mathematical models with multi-time delay, Alex. Eng. J., 59 (2020), 3149–3162. https://doi.org/10.1016/j.aej.2020.07.021 doi: 10.1016/j.aej.2020.07.021
    [27] M. Y. Ongun, The Laplace Adomian decomposition method for solving a model for HIV infection of CD4+ T cells, Math. Comput. Model., 53 (2011), 597–603. https://doi.org/10.1016/j.mcm.2010.09.009 doi: 10.1016/j.mcm.2010.09.009
    [28] M. Merdan, A. Gokdogan, A. Yildirim, On the numerical solution of the model for HIV infection of CD4+ T cells Comput. Math. Appl., 62 (2011) 118–123. https://doi.org/10.1016/j.camwa.2011.04.058
    [29] Ş. Yüzbaşı, A numerical approach to solve the model for HIV infection of CD4+ T cells, Appl. Math. Model., 36 (2012), 5876–5890. https://doi.org/10.1016/j.apm.2011.12.021 doi: 10.1016/j.apm.2011.12.021
    [30] N. Doğan, Numerical treatment of the model for HIV infection of CD4+ T cells by using multistep Laplace Adomian decomposition method, Discrete Dyn. Nat. Soci., 2012 (2012), 976352. https://doi.org/10.1155/2012/976352 doi: 10.1155/2012/976352
    [31] M.R. Gandomani, M. T. Kajani, Numerical solution of a fractional order model of HIV infection of CD4+ T cells using Müntz-Legendre polynomials, Inte. J. Bioautomation, 20 (2016), 193–204.
    [32] K. Parand, Z. Kalantari, M. Delkhosh, Quasilinearization-Lagrangian method to solve the HIV infection model of CD4+ T-cells, SeMA J., 75 (2018), 271–283. https://doi.org/10.1007/s40324-017-0133-1 doi: 10.1007/s40324-017-0133-1
    [33] Attaullah, R. Drissi, W. Weera, Galerkin time discretization scheme for the transmission dynamics of HIV infection with non-linear supply rate, AIMS Mathematics, 7 (2022), 11292–11310. https://doi.org/10.3934/math.2022630 doi: 10.3934/math.2022630
    [34] Z. Iqbal, N. Ahmed, D. Baleanu, W. Adel, M. Rafiq, M. A. ur Rehman, et al., Positivity and boundedness preserving numerical algorithm for the solution of fractional nonlinear epidemic model of HIV/AIDS transmission, Chaos Soliton. Fract., 134 (2020), 109706. https://doi.org/10.1016/j.chaos.2020.109706 doi: 10.1016/j.chaos.2020.109706
    [35] H. Günerhan, H. Dutta, M. A. Dokuyucu, W. Adel, Analysis of a fractional HIV model with Caputo and constant proportional Caputo operators, Chaos Soliton. Fract., 139 (2020), 110053. https://doi.org/10.1016/j.chaos.2020.110053 doi: 10.1016/j.chaos.2020.110053
    [36] W. Gao, H. Günerhan, H. Me. Baskonus, Analytical and approximate solutions of an epidemic system of HIV/AIDS transmission, Alex. Eng, J., 59 (2020), 3197–3211. https://doi.org/10.1016/j.aej.2020.07.043 doi: 10.1016/j.aej.2020.07.043
    [37] M. Sohaib, S. Haq, S. Mukhtar, I. Khan, Numerical solution of sixth-order boundary-value problems using Legendre wavelet collocation method, Res. Phys., 8 (2018), 1204–1208. https://doi.org/10.1016/j.rinp.2018.01.065 doi: 10.1016/j.rinp.2018.01.065
    [38] S. ul Islam, I. Aziz, A. S. Al-Fhaid, A. Shah, A numerical assessment of parabolic partial differential equations using Haar and Legendre wavelets, Appl. Math. Model., 37 (2013), 9455–9481. https://doi.org/10.1016/j.apm.2013.04.014 doi: 10.1016/j.apm.2013.04.014
    [39] M. H. Heydari, M. R. Hooshmandasl, F. M. M. Ghaini, C. Cattani, Wavelets method for the time fractional diffusion-wave equation, Phys. Lett. A, 379 (2015), 71–76. https://doi.org/10.1016/j.physleta.2014.11.012 doi: 10.1016/j.physleta.2014.11.012
    [40] M. H. Heydari, M. R. Hooshmandasl, F. M. M. Ghaini, F. Fereidouni, Two-dimensional Legendre wavelets for solving fractional Poisson equation with Dirichlet boundary conditions, Eng. Anal. Bound. Elem., 37(2013), 1331–1338. https://doi.org/10.1016/j.enganabound.2013.07.002 doi: 10.1016/j.enganabound.2013.07.002
    [41] K. Dizicheh, F. Ismail, M. T. Kajani, M. Maleki, A Legendre wavelet spectral collocation method for solving oscillatory initial value problems, J. Appl. Math., 2013 (2013), 591636. https://doi.org/10.1155/2013/591636 doi: 10.1155/2013/591636
    [42] M. T. Kajani, A. H. Vencheh, Solving linear integro-differential equation with Legendre wavelets, Int. J. Comput. Math., 81 (2004), 719–726. https://doi.org/10.1080/00207160310001650044 doi: 10.1080/00207160310001650044
    [43] D. Abbaszadeh, M. T. Kajani, M. Momeni, M. Zahraei, M. Maleki, Solving fractional Fredholm integro–differential equations using Legendre wavelets, Appl. Numer. Math., 166 (2021), 168–185. https://doi.org/10.1016/j.apnum.2021.04.008 doi: 10.1016/j.apnum.2021.04.008
    [44] M. Razzaghi, S. Yousefi, Legendre wavelets direct method for variational problems, Math. Comput. Simul., 53 (2020), 185–192. https://doi.org/10.1016/S0378-4754(00)00170-1 doi: 10.1016/S0378-4754(00)00170-1
    [45] M. Kutta, Beitrag zur naherungsweisen integration totaler differential gleichungen, Z. Math. Phys., 46 (1901), 435–453.
    [46] Attaullah, R. Jan, A. Jabeen, Solution of the HIV infection model with full logistic proliferation and variable source term using Galerkin scheme, Matrix Sci. Math., 4 (2020), 37–43. https://doi.org/10.26480/msmk.02.2020.37.43 doi: 10.26480/msmk.02.2020.37.43
    [47] X. Y. Zhou, X. Y. Song, X. Y. Shi, A differential equation model of HIV infection of CD4+ T-cells with cure rate, J. Math. Anal. Appl., 342 (2008), 1342–1355. https://doi.org/10.1016/j.jmaa.2008.01.008 doi: 10.1016/j.jmaa.2008.01.008
    [48] R. N. Nsubuga, R. G. White, B. N. Mayanja, L. A. Shafer, Estimation of the HIV basic reproduction number in rural south west Uganda: 1991–2008, Plos One, 9 (2014), e83778. https://doi.org/10.1371/journal.pone.0083778 doi: 10.1371/journal.pone.0083778
    [49] Z. M. Chen, X. X. Liu, L. L. Zeng, Threshold dynamics and threshold analysis of HIV infection model with treatment, Adv. Differ. Equ., 2020 (2020), 597. https://doi.org/10.1186/s13662-020-03057-2 doi: 10.1186/s13662-020-03057-2
    [50] J. W. Jia, G. L Qin, Stability analysis of HIV/AIDS epidemic model with nonlinear incidence and treatment, Adv. Differ. Equ., 2017(2017), 136. https://doi.org/10.1186/s13662-017-1175-5 doi: 10.1186/s13662-017-1175-5
    [51] H. L. Smith, Monotone dynamical systems: An introduction to the theory of competitive and cooperative systems, American Mathematical Society, 1995. https://doi.org/10.1090/surv/041
    [52] M. Y. Li, L. C. Wang, Global stability in some SEIR epidemic models. In: Mathematical approaches for emerging and reemerging infectious diseases: models, methods, and theory, New York: Springer, 2002,295–311. https://doi.org/10.1007/978-1-4613-0065-6_17
    [53] Attaullah, R. Jan, Ş. Yüzbaşı, Dynamical behaviour of HIV Infection with the influence of variable source term through Galerkin method, Chaos Soliton. Fract., 152 (2021), 111429. https://doi.org/10.1016/j.chaos.2021.111429 doi: 10.1016/j.chaos.2021.111429
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