Abstract
Though cell-to-cell transmission cannot be overlooked in HIV infection, many existing studies have only focused on the cell-free infection. Moreover, the infection rate is an important factor affecting viral transmission. Considering general incidence rates and latently infected cells, we develop an age-structured model with the two transmission modes. The expression of the basic reproduction number is derived. It turns out that the existence and local stability of equilibria is determined by the basic reproduction number. Before establishing the global dynamical behavior, we prove the existence of compact global attractors and uniform persistence. Then, by using the fluctuation lemma and Lyapunov functionals, a threshold dynamics is obtained. Saturated incidence rates are selected to simulate the relationship between latently infected cells and viruses, as well as the role of age-dependent parameters in infection.
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References
K. Manoj, A. Syed, Global dynamics of an age-structured model for HIV viral dynamics with latently infected T cells. Math. Comput. Simul. 198, 237–252 (2022)
J.H. Xu, Y. Geng, Y.C. Zhou, Global dynamics for an age-structured HIV virus infection model with cellular infection and antiretroviral therapy. Appl. Math. Comput. 305, 62–83 (2017)
A. Ishaku, A.M. Gazali, S.A. Abdullahi et al., Analysis and optimal control of an HIV model based on CD4 count. J. Math. Biol. 81, 209–241 (2020)
A.-H. Abdel-Aty, M.M.A. Khater, H. Dutta et al., 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, 110092 (2020)
WHO, HIV/AIDS, (2023). https://www.who.int/news-room/fact-sheets/detail/hiv-aids
D.X. Yan, X.L. Fu, Analysis of an age-structured HIV infection model with logistic target-cell growth and antiretroviral therapy. IMA J. Appl. Math. 83(6), 1037–1065 (2018)
N. Tarfulea, Drug therapy model with time delays for HIV infection with virus-to-cell and cell-to-cell transmissions. J. Appl. Math. Comput. 59, 677–691 (2019)
P. Aavani, L.J.S. Allen, The role of CD4+ T cells in immune system activation and viral reproduction in a simple model for HIV infection. Appl. Math. Model. 75, 210–222 (2019)
X. Wang, X.Y. Song, S.Y. Tang et al., Dynamics of an HIV model with multiple infection stages and treatment with different drug classes. Bull. Math. Biol. 78(2), 322–349 (2016)
X. Wang, Y.J. Lou, X.Y. Song, Age-structured within-host HIV dynamics with multiple target cells. Stud. Appl. Math. 138(1), 43–76 (2017)
Y. Gao, J.L. Wang, Threshold dynamics of a delayed nonlocal reaction–diffusion HIV infection model with both cell-free and cell-to-cell transmissions. J. Math. Anal. Appl. 488(1), 124047 (2020)
X.Q. Xie, J.L. Ma, P. van den Driessche, Backward bifurcation in within-host HIV models. Math. Biosci. 335, 108569 (2021)
M. Goyal, H.M. Baskonus, A. Prakash, Regarding new positive, bounded and convergent numerical solution of nonlinear time fractional HIV/AIDS transmission model. Chaos. Soliton. Fract. 139, 110096 (2020)
Y. Yang, L. Zou, S.G. Ruan, Global dynamics of a delayed within-host viral infection model with both virus-to-cell and cell-to-cell transmissions. Math. Biosci. 270, 183–191 (2015)
H.M. Doekes, C. Fraser, K.A. Lythgoe, Effect of the latent reservoir on the evolution of HIV at the within- and between-host levels. Plos. Comput. Biol. 13(1), e1005228 (2017)
A.M. Elaiw, A.D. Al Agha, S.A. Azoz et al., Global analysis of within-host SARS-CoV-2/HIV coinfection model with latency. Eur. Phys. J. Plus. 137, 174 (2022)
X. Wang, Y. Zhang, X.Y. Song, An age-structured epidemic model with waning immunity and general nonlinear incidence rate. Int. J. Biomath. 11(5), 1850069 (2018)
L. Shi, L. Wang, L. Zhu et al., Dynamics of an infection-age HIV diffusive model with latent infected cell and Beddington–DeAngelis infection incidence. Eur. Phys. J. Plus. 137, 212 (2022)
X. Wang, Y.M. Chen, M. Martcheva et al., Asymptotic analysis of a vector-borne disease model with the age of infection. J. Biol. Dyn. 14(1), 332–367 (2020)
X.M. Feng, S.G. Ruan, T.Z. Teng et al., Stability and backward bifurcation in a malaria transmission model with applications to the control of malaria in China. Math. Biosci. 266, 52–64 (2015)
X. Wang, Y.M. Chen, X.Y. Song, Global dynamics of a cholera model with age structures and multiple transmission modes. Int. J. Biomath. 12(5), 1950051 (2019)
J.Z. Lin, R. Xu, X.H. Tian, Global dynamics of an age-structured cholera model with both human-to-human and environment-to-human transmissions and saturation incidence. Appl. Math. Model. 63, 688–708 (2018)
X. Wang, Y.M. Chen, S.Q. Liu, Global dynamics of a vector-borne disease model with infection ages and general incidence rates. Comput. Appl. Math. 37, 4055–4080 (2018)
L.M. Agosto, P.D. Uchil, W. Mothes, HIV cell-to-cell transmission: effects on pathogenesis and antiretroviral therapy. Trends Microbiol. 23(5), 289–295 (2015)
A. Alshorman, C. Samarasinghe, W.L. Lu et al., An HIV model with age-structured latently infected cells. J. Biol. Dyn. 11(sup1), 192–215 (2017)
J.L. Wang, J.Y. Lang, X.F. Zou, Analysis of an age structured HIV infection model with virus-to-cell infection and cell-to-cell transmission. Nonlinear. Anal. Real 34, 75–96 (2017)
J.N. Blankson, D. Persaud, R.F. Siliciano, The challenge of viral reservoirs in HIV-1 infection. Annu. Rev. Med. 53(1), 557–593 (2002)
C.Y. Qin, X. Wang, L.B. Rong, An age-structured model of HIV latent infection with two transmission routes: analysis and optimal control. Complexity 2020, 1890320 (2020). https://doi.org/10.1155/2020/1890320
C.J. Browne, S.S. Pilyugin, Global analysis of age-structured within-host virus model. Discrete. Cont. Dyn B. 18(8), 1999–2017 (2013)
P. Magal, Compact attractors for time periodic age-structured population models. Electron. J. Differ. Equ. 65, 1–35 (2001)
M. Martcheva, H.R. Thieme, Progression age enhanced backward bifurcation in an epidemic model with super-infection. J. Math. Biol. 46(5), 385–424 (2003)
W.M. Hirsch, H. Hanisch, J.P. Gabriel, Differential equation models of some parasitic infections: methods for the study of asymptotic behavior. Commun. Pur. Appl. Math. 38(6), 733–753 (1985)
S. Bentout, Y.M. Chen, S. Djilali, Global dynamics of an SEIR model with two age structures and a nonlinear incidence. Acta. Appl. Math. 171(1), 7 (2021). https://doi.org/10.1007/s10440-020-00369-z
H.L. Smith, H.R. Thieme, Dynamical Systems and Population Persistence (American Mathematical Society, Providence, 2011), pp.126–379
A. Alshorman, X. Wang, M. Joseph-Meyer et al., Analysis of HIV models with two time delays. J. Biol. Dyn. 11(sup1), 40–64 (2017)
X. Wang, S.Y. Tang, X.Y. Song et al., Mathematical analysis of an HIV latent infection model including both virus-to-cell infection and cell-to-cell transmission. J. Biol. Dyn. 11(sup2), 455–483 (2017)
X. Wang, Y.M. Chen, S.Q. Liu, Dynamics of an age-structured host-vector model for malaria transmission. Math. Method. Appl. Sci. 41(5), 1966–1987 (2018)
Acknowledgements
This work is supported partially by the National Natural Science Foundation of China (No. 12171413), the Natural Science Foundation of Henan Province (222300420016), and the Program for Science and Technology Innovation Teams in Henan (21IRTSTHN014), and the Scientific Research Foundation of Graduate School of Xinyang Normal University (No. 2022KYJJ010).
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Li, J., Wang, X. & Chen, Y. Analysis of an age-structured HIV infection model with cell-to-cell transmission. Eur. Phys. J. Plus 139, 78 (2024). https://doi.org/10.1140/epjp/s13360-024-04873-1
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DOI: https://doi.org/10.1140/epjp/s13360-024-04873-1