This work investigates the dynamics of a diffusive viral infection model that incorporates a nonlinear incidence and follicular dendritic cells (FDCs). First, the well-posedness is established. Then, We show that the basic reproduction number serves as a critical threshold for global stabilities: the infection-free steady state is globally asymptotically stable when the basic reproduction number is less than one, while the model exhibits a uniform persistence when the basic reproduction number is greater than one. Under the condition that the basic reproduction number equals to one, the infection-free steady state is shown to be globally asymptotically stable given certain additional assumptions. Furthermore, the global stability of the infected steady state is established for the homogeneous case. We find that ignoring the spatial heterogeneity in the infection capacity of viruses and infected cells may lead to an underestimation of the transmission risk. Although the spatial heterogeneity of a FDC does not affect the basic reproduction number, neglecting the infection originating from a FDC may lead to an underestimation of the infection risk.
Citation: Yan Geng, Jinhu Xu. Spatial dynamics of a viral infection model with nonlinear incidence rate[J]. Electronic Research Archive, 2026, 34(3): 1691-1719. doi: 10.3934/era.2026077
This work investigates the dynamics of a diffusive viral infection model that incorporates a nonlinear incidence and follicular dendritic cells (FDCs). First, the well-posedness is established. Then, We show that the basic reproduction number serves as a critical threshold for global stabilities: the infection-free steady state is globally asymptotically stable when the basic reproduction number is less than one, while the model exhibits a uniform persistence when the basic reproduction number is greater than one. Under the condition that the basic reproduction number equals to one, the infection-free steady state is shown to be globally asymptotically stable given certain additional assumptions. Furthermore, the global stability of the infected steady state is established for the homogeneous case. We find that ignoring the spatial heterogeneity in the infection capacity of viruses and infected cells may lead to an underestimation of the transmission risk. Although the spatial heterogeneity of a FDC does not affect the basic reproduction number, neglecting the infection originating from a FDC may lead to an underestimation of the infection risk.
| [1] |
A. S. Perelson, D. E. Kirschner, R. De Boer, Dynamics of HIV infection of CD4$^+$ T cells, Math. Biosci., 114 (1993), 81–125. https://doi.org/10.1016/0025-5564(93)90043-A doi: 10.1016/0025-5564(93)90043-A
|
| [2] |
S. Bonhoeffer, R. M. May, G. M. Shaw, M. A. Nowak, Virus dynamics and drug therapy, Proc. Nat. Acad. Sci., 94 (1997), 6971–6976. https://doi.org/10.1073/pnas.94.13.6971 doi: 10.1073/pnas.94.13.6971
|
| [3] |
O. Nave, Modification of semi-analytical method applied system of ODE, Mod. Appl. Sci., 14 (2020), 75–81. https://doi.org/10.5539/mas.v14n6p75 doi: 10.5539/mas.v14n6p75
|
| [4] |
A. Korobeinikov, Global properties of basic virus dynamics models, Bull. Math. Biol., 66 (2004), 879–883. https://doi.org/10.1016/j.bulm.2004.02.001 doi: 10.1016/j.bulm.2004.02.001
|
| [5] |
D. Finzi, M. Hermankova, T. Pierson, L. M. Carruth, C. Buck, R. E. Chaisson, et al., Identification of a reservoir for HIV-1 in patients on highly active antiretroviral therapy, Science, 278 (1997), 1295–1300. https://doi.org/10.1126/science.278.5341.1295 doi: 10.1126/science.278.5341.1295
|
| [6] |
B. Heesters, M. Lindqvist, P. A. Vagefi, E. P. Scully, F. A. Schildberg, M. Altfeld, et al., Follicular dendritic cells retain infectious HIV in cycling endosomes, PLoS Pathog., 11 (2015), e1005285. https://doi.org/10.1371/journal.ppat.1005285 doi: 10.1371/journal.ppat.1005285
|
| [7] |
A. T. Haase, K. Henry, M. Zupancic, G. Sedgewick, R. A. Faust, H. Melroe, et al., Quantitative image analysis of HIV-1 infection in lymphoid tissue, Science, 274 (1996), 985–989. https://doi.org/10.1126/science.274.5289.985 doi: 10.1126/science.274.5289.985
|
| [8] |
B. A. Smith, S. Gartner, Y. Liu, A. S. Perelson, N. I. Stilianakis, B. F. Keele, et al., Persistence of infectious HIV on follicular dendritic cells, J. Immunol., 166 (2001), 690–696. https://doi.org/10.4049/jimmunol.166.1.690 doi: 10.4049/jimmunol.166.1.690
|
| [9] |
T. C. Thacker, X. Zhou, J. D. Estes, Y. Jiang, B. F. Keele, T. S. Elton, et al., Follicular dendritic cells and human immunodeficiency virus type 1 transcription in CD4+ T cells, J. Virol., 83 (2009), 150–158. https://doi.org/10.1128/jvi.01652-08 doi: 10.1128/jvi.01652-08
|
| [10] |
J. Zhang, A. S. Perelson, Contribution of follicular dendritic cells to persistent HIV viremia, J. Virol., 87 (2013), 7893–7901. https://doi.org/10.1128/jvi.00556-13 doi: 10.1128/jvi.00556-13
|
| [11] |
F. Sabri, A. Prados, R. Munoz-Fernandez, R. Lantto, P. Fernandez-Rubio, A. Nasi, et al., Impaired B cells survival upon production of inflammatory cytokines by HIV-1 exposed follicular dendritic cells, Retrovirology, 13 (2016), 61. https://doi.org/10.1186/s12977-016-0295-4 doi: 10.1186/s12977-016-0295-4
|
| [12] |
C. V. Fletcher, K. Staskus, S. W. Wietgrefe, M. Rothenberger, C. Reilly, J. G. Chipman, et al., Persistent HIV-1 replication is associated with lower antiretroviral drug concentrations in lymphatic tissues, Proc. Natl. Acad. Sci., 111 (2014), 2307–2312. https://doi.org/10.1073/pnas.1318249111 doi: 10.1073/pnas.1318249111
|
| [13] |
M. T. Ollerton, E. A. Berger, E. Connick, G. F. Burton, HIV-1-specific chimeric antigen receptor T cells fail to recognize and eliminate the follicular dendritic cell HIV reservoir in vitro, J. Virol., 94 (2020), e00190-20. https://doi.org/10.1128/jvi.00190-20 doi: 10.1128/jvi.00190-20
|
| [14] |
W. S. Hlavacek, C. Wofsy, A. S. Perelson, Dissociation of HIV-1 from follicular dendritic cells during HAART: mathematical analysis, Proc. Nat. Acad. Sci., 96 (1999), 14681–14686. https://doi.org/10.1073/pnas.96.26.14681 doi: 10.1073/pnas.96.26.14681
|
| [15] |
W. S. Hlavacek, N. I. Stilianakis, D. W. Notermans, S. A. Danner, A. S. Perelson, Influence of follicular dendritic cells on decay of HIV during antiretroviral therapy, Proc. Nat. Acad. Sci., 97 (2000), 10966–10971. https://doi.org/10.1073/pnas.190065897 doi: 10.1073/pnas.190065897
|
| [16] |
D. S. Callaway, A. S. Perelson, HIV-1 infection and low steady state viral loads, Bull. Math. Biol., 64 (2002), 29–64. https://doi.org/10.1006/bulm.2001.0266 doi: 10.1006/bulm.2001.0266
|
| [17] |
Y. Geng, J. Xu, Modelling and analysis of a delayed viral infection model with follicular dendritic cell, Electron. Res. Arch., 32 (2024), 5127–5138. https://doi.org/10.3934/era.2024236 doi: 10.3934/era.2024236
|
| [18] |
W. Wang, T. Zhang, Caspase-1-mediated pyroptosis of the predominance for driving CD4+ T cells death: A nonlocal spatial mathematical model, Bull. Math. Biol., 80 (2018), 540–582. https://doi.org/10.1007/s11538-017-0389-8 doi: 10.1007/s11538-017-0389-8
|
| [19] |
W. Wang, X. Wang, X. Fan, On the global attractivity of a diffusive viral infection model with spatial heterogeneity, Math. Method Appl. Sci., 48 (2025), 15656–15660. https://doi.org/10.1002/mma.70040 doi: 10.1002/mma.70040
|
| [20] |
Y. Jiang, T. Zhang, Global stability of a cytokine-enhanced viral infection model with nonlinear incidence rate and time delays, Appl. Math. Letter., 132 (2022), 108110. https://doi.org/10.1016/j.aml.2022.108110 doi: 10.1016/j.aml.2022.108110
|
| [21] |
W. Wang, G. Wu, X. Fan, Global dynamics of a novel viral infection model mediated by pattern recognition receptors, Appl. Math. Lett. 173 (2026), 109757. https://doi.org/10.1016/j.aml.2025.109757 doi: 10.1016/j.aml.2025.109757
|
| [22] |
A. D. Portillo, J. Tripodi, V. Najfeld, D. Wodarz, D. N. Levy, B. K. Chen, Multiploid inheritance of HIV-1 during cell-to-cell infection, J. Virol., 85 (2011), 7169–7176. https://doi.org/10.1128/JVI.00231-11 doi: 10.1128/JVI.00231-11
|
| [23] |
H. Sato, J. Orenstein, D. S. Dimitrov, M. Martin, Cell-to-cell spread of HIV-1 occurs with minutes and may not involve the participation of virus particles, Virology, 186 (1992), 712–724. https://doi.org/10.1016/0042-6822(92)90038-q doi: 10.1016/0042-6822(92)90038-q
|
| [24] |
R. V. Culshaw, S. Ruan, G. Webb, A mathematical model of cell-to-cell spread of HIV-1 that includes a time delay, J. Math. Biol., 46 (2003), 425–444. https://doi.org/10.1007/s00285-002-0191-5 doi: 10.1007/s00285-002-0191-5
|
| [25] |
Y. Yang, L. Zou, S. Ruan, Global dynamics of a delayed within-host viral infection model with both virus-to-cell and cell-to-cell transmissions, Math. Biosci., 270 (2015), 183–191. https://doi.org/10.1016/j.mbs.2015.05.001 doi: 10.1016/j.mbs.2015.05.001
|
| [26] |
X. Lai, X. Zou, Modeling HIV-1 virus dynamics with both virus-to-cell infection and cell-to-cell transmission, SIAM J. Appl. Math., 74 (2014), 898–917. https://doi.org/10.1137/130930145 doi: 10.1137/130930145
|
| [27] |
J. Wang, J. Yang, T. Kuniya, Dynamics of a PDE viral infection model incorporating cell-to-cell transmission, J. Math. Anal. Appl., 444 (2016), 1542–1564. https://doi.org/10.1016/j.jmaa.2016.07.027 doi: 10.1016/j.jmaa.2016.07.027
|
| [28] |
X. Ren, Y. Tian, L. Liu, X. Liu, A reaction–diffusion within-host HIV model with cell-to-cell transmission, J. Math. Biol., 76 (2018), 1831–1872. https://doi.org/10.1007/s00285-017-1202-x doi: 10.1007/s00285-017-1202-x
|
| [29] |
Y. Wang, T. Zhao, J. Liu, Viral dynamics of an HIV stochastic model with cell-to-cell infection, CTL immune response and distributed delays, Math. Biosci. Eng., 16 (2019), 7126–7154. https://doi.org/10.3934/mbe.2019358 doi: 10.3934/mbe.2019358
|
| [30] |
H. Miao, M. Jiao, Spatial dynamics of a delayed viral infection model with two modes of transmission and immune impairment, Discrete Dyn. Nat. Soc., 2022 (2022), 9531450. https://doi.org/10.1155/2022/9531450 doi: 10.1155/2022/9531450
|
| [31] |
J. Wang, J. Lang, X. Zou, Analysis of an age structured HIV infection model with both virus-to-cell infection and cell-to-cell transmission, Nonlinear Anal. Real World Appl., 34 (2017), 75–96. https://doi.org/10.1016/j.nonrwa.2016.08.001 doi: 10.1016/j.nonrwa.2016.08.001
|
| [32] |
X. Zhang, Z. Liu, Bifurcation analysis of an age structured HIV infection model with both virus-to-cell and cell-to-cell transmissions, Int. J. Bifurcation Chaos, 28 (2018), 1850109. https://doi.org/10.1142/S0218127418501092 doi: 10.1142/S0218127418501092
|
| [33] |
C. Cheng, Y. Dong, Y. Takeuchi, An age-structured virus model with two routes of infection in heterogeneous environments, Nonlinear Anal. Real World Appl., 39 (2018), 464–491. https://doi.org/10.1016/j.nonrwa.2017.07.013 doi: 10.1016/j.nonrwa.2017.07.013
|
| [34] |
A. M. Elaiw, N. H. AlShamrani, Global stability of a delayed adaptive immunity viral infection with two routes of infection and multi-stages of infected cells, Commun. Nonlinear. Sci. Numer. Simul., 86 (2020), 105259. https://doi.org/10.1016/j.cnsns.2020.105259 doi: 10.1016/j.cnsns.2020.105259
|
| [35] |
J. Deng, H. Shu, L. Wang, X. S. Wang, Viral dynamics with immune responses: Effects of distributed delays and Filippov antiretroviral therapy, J. Math. Biol. 86 (2023), 37. https://doi.org/10.1007/s00285-023-01869-w doi: 10.1007/s00285-023-01869-w
|
| [36] | F. Graw, A. S. Perelson, Spatial aspects of HIV infection, in Mathematical methods and models in biomedicine, Springer, (2012), 3–31. https://doi.org/10.1007/978-1-4614-4178-6_1 |
| [37] |
Y. Lou, X. Zhao, A reaction-diffusion malaria model with incubation period in the vector population, J. Math. Biol. 62 (2011), 543–568. https://doi.org/10.1007/s00285-010-0346-8 doi: 10.1007/s00285-010-0346-8
|
| [38] |
X. Lai, X. Zou, Repulsion effect on superinfecting virions by infected cells, Bull. Math. Biol. 76 (2014), 2806–2833. https://doi.org/10.1007/s11538-014-0033-9 doi: 10.1007/s11538-014-0033-9
|
| [39] |
H. Shu, Z. Ma, X. Wang, L. Wang, Viral diffusion and cell-to-cell transmission: Mathematical analysis and simulation study, J. Math. Pures Appl., 137 (2020), 290–313. https://doi.org/10.1016/j.matpur.2020.03.011 doi: 10.1016/j.matpur.2020.03.011
|
| [40] |
Z. Li, X. Zhao, Global dynamics of a time-delayed nonlocal reaction-diffusion model of within-host viral infections, J. Math. Biol., 88 (2024), 38. https://doi.org/10.1007/s00285-024-02052-5 doi: 10.1007/s00285-024-02052-5
|
| [41] | H. Smith, Monotone Dynamical Systems: An Introduction to The Theory of Competitive and Cooperative Systems, American Mathematical Society, 1995. |
| [42] |
R. H. Martin, H. Smith, Abstract functional differential equations and reaction-diffusion systems, Trans. Amer. Math. Soc., 321 (1990), 1–44. https://doi.org/10.1090/S0002-9947-1990-0967316-X doi: 10.1090/S0002-9947-1990-0967316-X
|
| [43] |
Z. Guo, F. Wang, X. Zou, Threshold dynamics of an infective disease model with a fixed latent period and nonlocal infections, J. Math. Biol., 65 (2012), 1387–1410. https://doi.org/10.1007/s00285-011-0500-y doi: 10.1007/s00285-011-0500-y
|
| [44] | Y. Du, Order Structure and Topological Methods in Nonlinear Partial Differential Equations, World Scientific, 2006. |
| [45] | R. Guenther, J. Lee, Partial Differential Equations of Mathematical Physics and Integral Equations, Courier Corporation, 1996. |
| [46] | M. Wang, Nonlinear Elliptic Equations (in Chinese), Science Press, 2010. |
| [47] | J. Wu, Theory and Applications of Partial Functional Differential Equations, Springer, 1996. https://doi.org/10.1007/978-1-4612-4050-1 |
| [48] | J. Hale, Asymptotic Behavior of Dissipative Systems, American Mathematical Society, 1988. |
| [49] |
W. Wang, X. Zhao, Basic reproduction numbers for reaction-diffusion epidemic models, SIAM J. Appl. Dyn. Syst., 11 (2012), 1652–1673. https://doi.org/10.1137/120872942 doi: 10.1137/120872942
|
| [50] |
H. Thieme, Spectral bound and reproduction number for infinite-dimensional population structure and time heterogeneity, SIAM J. Appl. Math., 70 (2009), 188–211. https://doi.org/10.1137/080732870 doi: 10.1137/080732870
|
| [51] | W. Desch, W. Schappacher, Linearized stability for nonlinear semigroups, in Differential Equations in Banach Spaces, Springer, (1986), 61–73. |
| [52] |
H. Thieme, Convergence results and a Poincar-Bendixson trichotomy for asymptotically autonomous differential equations, J. Math. Biol., 30 (1992), 755–763. https://doi.org/10.1007/BF00173267 doi: 10.1007/BF00173267
|
| [53] |
Y. Yang, J. Zhou, C. Hsu, Threshold dynamics of a diffusive SIRI model with nonlinear incidence rate, J. Math. Anal. Appl., 478 (2019), 874–896. https://doi.org/10.1016/j.jmaa.2019.05.059 doi: 10.1016/j.jmaa.2019.05.059
|
| [54] | M. Protter, H. Weinberger, Maximum Principles in Differential Equations, Springer, 1984. |
| [55] |
H. Smith, X. Zhao, Robust persistence for semidynamical systems, Nonlinear Anal. Theory Methods Appl., 47 (2001), 6169–6179. https://doi.org/10.1016/S0362-546X(01)00678-2 doi: 10.1016/S0362-546X(01)00678-2
|
| [56] |
P. Magal, X. Zhao, Global attractors and steady states for uniformly persistent dynamical systems, SIAM J. Math. Anal., 37 (2005), 251–275. https://doi.org/10.1137/S0036141003439173 doi: 10.1137/S0036141003439173
|
| [57] |
P. Magal, G. Webb, Y. Wu, On a vector-host epidemic model with spatial structure, Nonlinearity, 31 (2018), 5589–5614. https://doi.org/10.1088/1361-6544/aae1e0 doi: 10.1088/1361-6544/aae1e0
|
| [58] |
Y. Wu, X. Zou, Dynamics and profiles of a diffusive host-pathogen system with distinct dispersal rates, J. Differ. Equations, 264 (2018), 4989–5024. https://doi.org/10.1016/j.jde.2017.12.027 doi: 10.1016/j.jde.2017.12.027
|
| [59] | P. Hess, Periodic-Parabolic Boundary Value Problems and Positivity, Longman Scientific and Technical, 1991. |
| [60] | G. Webb, Theory of Nonlinear Age-Dependent Population Dynamics, CRC Press, 1985. |