Research article

An age-structured epidemic model with boosting and waning of immune status

  • Received: 10 April 2021 Accepted: 03 June 2021 Published: 24 June 2021
  • In this paper, we developed an age-structured epidemic model that takes into account boosting and waning of immune status of host individuals. For many infectious diseases, the immunity of recovered individuals may be waning as time evolves, so reinfection could occur, but also their immune status could be boosted if they have contact with infective agent. According to the idea of the Aron's malaria model, we incorporate a boosting mechanism expressed by reset of recovery-age (immunity clock) into the SIRS epidemic model. We established the mathematical well-posedness of our formulation and showed that the initial invasion condition and the endemicity can be characterized by the basic reproduction number $ R_0 $. Our focus is to investigate the condition to determine the direction of bifurcation of endemic steady states bifurcated from the disease-free steady state, because it is a crucial point for disease prevention strategy whether there exist subcritical endemic steady states. Based on a recent result by Martcheva and Inaba [1], we have determined the direction of bifurcation that endemic steady states bifurcate from the disease-free steady state when the basic reproduction number passes through the unity. Finally, we have given a necessary and sufficient condition for backward bifurcation to occur.

    Citation: Kento Okuwa, Hisashi Inaba, Toshikazu Kuniya. An age-structured epidemic model with boosting and waning of immune status[J]. Mathematical Biosciences and Engineering, 2021, 18(5): 5707-5736. doi: 10.3934/mbe.2021289

    Related Papers:

  • In this paper, we developed an age-structured epidemic model that takes into account boosting and waning of immune status of host individuals. For many infectious diseases, the immunity of recovered individuals may be waning as time evolves, so reinfection could occur, but also their immune status could be boosted if they have contact with infective agent. According to the idea of the Aron's malaria model, we incorporate a boosting mechanism expressed by reset of recovery-age (immunity clock) into the SIRS epidemic model. We established the mathematical well-posedness of our formulation and showed that the initial invasion condition and the endemicity can be characterized by the basic reproduction number $ R_0 $. Our focus is to investigate the condition to determine the direction of bifurcation of endemic steady states bifurcated from the disease-free steady state, because it is a crucial point for disease prevention strategy whether there exist subcritical endemic steady states. Based on a recent result by Martcheva and Inaba [1], we have determined the direction of bifurcation that endemic steady states bifurcate from the disease-free steady state when the basic reproduction number passes through the unity. Finally, we have given a necessary and sufficient condition for backward bifurcation to occur.



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    [1] M. Martcheva, H. Inaba, A Lyapunov-Schmidt method for detecting backward bifurcation in age-structured population models, J. Biol. Dyn., 14 (2020), 543–565. doi: 10.1080/17513758.2020.1785024
    [2] W. O. Kermack, A. G. McKendrick, Contributions to the mathematical theory of epidemics II. The problem of endemicity, Proc. Roy. Soc., 138A (1932), 55–83.
    [3] H. Inaba, Endemic threshold analysis for the Kermack–McKendrick reinfection model, Josai Math. Monographs, 9 (2016), 105–133.
    [4] H. Inaba, Age-Structured Population Dynamics in Demography and Epidemiology, Springer, 2017.
    [5] S. Bhattacharya, F. R. Adler, A time since recovery model with varying rates of loss of immunity, Bull. Math. Biol., 74 (2012), 2810–2819. doi: 10.1007/s11538-012-9780-7
    [6] Y. Nakata, Y. Enatsu, H. Inaba, T. Kuniya, Y. Muroya, Y. Takeuchi, Stability of epidemic models with waning immunity, SUT J. Math., 50 (2014), 205–245.
    [7] K. Okuwa, H. Inaba, T. Kuniya, Mathematical analysis for an age-structured SIRS epidemic model, Math. Biosci. Eng., 16 (2019), 6071–6102. doi: 10.3934/mbe.2019304
    [8] J. M. Heffernan, M. J. Keeling, Implications of vaccination and waning immunity, Proc. Roy. Soc. B, 276 (2009), 2071–2080. doi: 10.1098/rspb.2009.0057
    [9] F. Kambiré, E. Gouba, S. Tao, B. Somé, Mathematical analysis of an immune-structured chikungunya transmission model, Eur. J. Pur. Appl. Math., 12 (2019), 1533–1552. doi: 10.29020/nybg.ejpam.v12i4.3532
    [10] T. Leung, B. D. Hughes, F. Frascoli, J. M. McCaw, Periodic solutions in an SIRWS model with immune boosting and cross-immunity, J. Theor. Biol., 410 (2016), 55–64. doi: 10.1016/j.jtbi.2016.08.034
    [11] T. Leung, P. T. Cambell, B. D. Hughes, F. Frascoli, J. M. McCaw, Infection-acquired versus vaccine-acquired immunity in an SIRWS model, Infectious Diseases Modelling, 3 (2018), 118–135. doi: 10.1016/j.idm.2018.06.002
    [12] M. P. Dafilis, F. Frascoli, J. G. Wood, J. M. Mccaw, The influence of increasing life expectancy on the dynamics of SIRS systems with immune boosting, ANZIAM J., 54 (2012), 50–63. doi: 10.1017/S1446181113000023
    [13] O. Diekmann, W. E. de Graaf, M. E. E. Kretzschmar, P. F. M. Teunis, Waning and boosting: On the dynamics of immune status, J. Math. Biol., 77 (2018), 2023–2048. doi: 10.1007/s00285-018-1239-5
    [14] F. M. G. Magpantay, M. A. Riolo, M. D. de Cellès, A. A. King, P. Rohani, Epidemiological consequences of imperfect vaccines for immunizing infections, SIAM J. Appl. Math., 74 (2014), 1810–1830. doi: 10.1137/140956695
    [15] J. L. Aron, Dynamics of acquired immunity boosted by exposure to infection, Math. Biosci., 64 (1983), 249–259. doi: 10.1016/0025-5564(83)90007-X
    [16] J. L. Aron, Acquired immunity dependent upon exposure in an SIRS epidemic model, Math. Biosci., 88 (1988), 37–47. doi: 10.1016/0025-5564(88)90047-8
    [17] J. L. Aron, Mathematical modelling of immunity of malaria, Math. Biosci., 90 (1988), 385–396. doi: 10.1016/0025-5564(88)90076-4
    [18] M. V. Barbarossa, G. Röst, Immuno-epidemiology of a population structured by immune status: A mathematical study of waning immunity and immune system boosting, J. Math. Biol., 71 (2015), 1737–1770. doi: 10.1007/s00285-015-0880-5
    [19] M. V. Barbarossa, M. Polner, G. Röst, Temporal evolution of immunity distributions in a population with waning and boosting, Complexity, 2018, Article ID 9264743.
    [20] M. Martcheva, S. S. Pilyugin, An epidemic model structured by host immunity, J. Biol. Sys., 14 (2006), 185–203. doi: 10.1142/S0218339006001787
    [21] O. Diekmann, J. A. P. Heesterbeak, J. A. J. Metz, On the definition and the computation of the basic reproduction ratio $R_0$ in models for infectious diseases in heterogeneous populations, J. Math. Biol., 28 (1990), 365–382.
    [22] H. Inaba, The basic reproduction number $R_0$ in time-heterogeneous environments, J. Math. Biol., 79 (2019), 731–764. doi: 10.1007/s00285-019-01375-y
    [23] H. Inaba, Endemic threshold results in an age-duration-structured population model for HIV infection, Math. Biosci., 201 (2006), 15–47. doi: 10.1016/j.mbs.2005.12.017
    [24] P. Magal, C. C. McCluskey, G. F. Webb, Lyapunov functional and global asymptotic stability for an infection-age model, Appl. Anal., 89 (2010), 1109–1140. doi: 10.1080/00036810903208122
    [25] H. R. Thieme, Semiflows generated by Lipschitz perturbations of non-densely defined operators, Diff. Inte. Equ., 3 (1990), 1035–1066.
    [26] H. L. Smith, H. R. Thieme Dynamical Systems and Population Persistence, Amer. Math. Soc., 2013.
    [27] G. Da Prato, E. Sinestrari, Differential operators with non dense domain, Annali della Scuola Normale Superiore di Pisa, 14 (1987), 285–344.
    [28] G. F. Webb, Theory of Nonlinear Age-Dependent Population Dynamics, Mercel Dekker, New York, 1985.
    [29] Ph. Clément, H. J. A. M. Heijmans, S. Angenent C. J. van Duijn, B. de Pagter, One-Parameter Semigroups, CWI monographs, Volume 5, North-Holland Publishing Company, 1987.
    [30] A. Ducrot, Z. Liu, P. Magal, Essential growth rate for bounded linear perturbation of non-densely defined Cauchy problems, J. Math. Anal. Appl., 341 (2008), 501–518. doi: 10.1016/j.jmaa.2007.09.074
    [31] N. F. Britton, Reaction–Diffusion Equations and Their Applications to Biology, Academic Press, London, 1986.
    [32] L. Yang, Y. Nakata, Note on the uniqueness of an endemic equilibrium of an epidemic model with boosting of immunity, J. Biol. Sys., 29 (2021), 1–12. doi: 10.1142/S0218339021500017
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