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Nested Immuno-Epidemiological Models

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Age Structured Epidemic Modeling

Part of the book series: Interdisciplinary Applied Mathematics ((IAM,volume 52))

Abstract

Immuno-epidemiological modeling of infectious diseases is a technique that links a within-host mathematical model with a between-host mathematical model. In the simplest nested models the within-host model is an ODE structured by the time since infection. The between-host model is a time-since-infection and chronological time structured PDE. The nested immuno-epidemiological are related to age-since-infection models that we consider in Chap. 8. The linking between the two models consists in two parts: linking through the time-since-infection and linking through the parameters of the epidemiological model which depend on the within-host variables. It is very important that the within-host model and the between-host model are consistent. For instance, if the disease is chronic, the within-host model should lead to chronic infection, that is have a stable infected equilibrium, and the between-host model should contain no recovered class. Such is the case with HIV. On the other hand, if the disease always leads to recovery, the within-host model should be an outbreak model, while the between-host model should have a recovered class. This scenario is appropriate for diseases such as influenza.

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References

  1. R. Ben-Shachar, K. Koelle, Minimal within-host dengue models highlight the specific roles of the immune response in primary and secondary dengue infections. J. R. Soc. Interface 12, 20140886 (2015)

    Article  Google Scholar 

  2. S. Bhattacharya, M. Martcheva, An immuno-eco-epidemiological model of competition. J. Biol. Dyn. 10, 314–341 (2016)

    Article  MathSciNet  Google Scholar 

  3. D. Coombs, M.A. Gilchrist, C. Ball, Evaluating the importance of within- and between-host selection pressures on the evolution of chronic pathogens. Theor. Popul. Biol. 72, 576–591 (2007)

    Article  Google Scholar 

  4. Y.-X. Dang, X.-Z. Li, M. Martcheva, Competitive exclusion in a multi-strain immuno-epidemiological influenza model with environmental transmission. J. Biol. Dyn. 10, 416–456 (2016)

    Article  MathSciNet  Google Scholar 

  5. Z. Feng, H.R. Thieme, Recurrent outbreaks of childhood diseases revisited: the impact of isolation. Math. Biosci. 128, 93–130 (1995)

    Article  MathSciNet  Google Scholar 

  6. R.S. Fritz, F.G. Hayden, D.P. Calfee, L.M.R. Cass, A.W. Peng, W.G. Alvord, W. Strober, S.E. Straus, Nasal cytokine and chemokine responses in experimental influenza a virus infection: Results of a placebo-controlled trial of intravenous zanamivir treatment. J. Infect. Dis. 180, 586–593 (1999)

    Article  Google Scholar 

  7. M.A. Gilchrist, D. Coombs, Evolution of virulence: interdependence, constraints, and selection using nested models. Theor. Popul. Biol. 69, 145–153 (2006)

    Article  Google Scholar 

  8. M.A. Gilchrist, A. Sasaki, Modeling host-parasite coevolution: a nested approach based on mechanistic models. J. Theor. Biol. 218, 289–308 (2002)

    Article  MathSciNet  Google Scholar 

  9. M.G. Guzman et al., Dengue: a continuing global threat. Nat. Rev. Microbiol. 8, S7–S16 (2010)

    Article  Google Scholar 

  10. M. Iannelli, Mathematical Theory of Age-Structured Population Dynamics (Giardini, Pisa, 1995)

    Google Scholar 

  11. M. Iannelli, F. Milner, The Basic Approach to Age-Structured Population Dynamics (Springer, New York, 2017)

    Book  Google Scholar 

  12. I. Kawaguchi, A. Sasaki, M. . Boots, Why are dengue virus serotypes so distantly related? Enhancement and limiting serotype similarity between dengue virus strains. Proc. Biol. Sci. 270, 2241–2247 (2003)

    Google Scholar 

  13. M. Martcheva, An Introduction to Mathematical Epidemiology. Texts in Applied Mathematics, vol. 61 (Springer, New York, 2015)

    Book  Google Scholar 

  14. M. Martcheva, X.-Z. Li, Linking immunological and epidemiological dynamics of HIV: the case of super-infection. J. Biol. Dyn. 7, 161–182 (2013)

    Article  MathSciNet  Google Scholar 

  15. F.A. Milner, A. Pugliese, Periodic solutions: a robust numerical method for an S-I-R model of epidemics. J. Math. Biol. 39, 471–492 (1999)

    Article  MathSciNet  Google Scholar 

  16. N.M. Nguyen, et al., Host and viral features of human dengue cases shape the population of infected and infectious aedes aegypti mosquitoes. Proc. Natl Acad. Sci. USA 110, 9072–9077 (2013)

    Article  Google Scholar 

  17. E. Numfor, S. Bhattacharya, S. Lenhart, M. Martcheva, Optimal control in coupled within-host and between-host models. Math. Model. Nat. Phenom. 9, 171–203 (2014)

    Article  MathSciNet  Google Scholar 

  18. E. Numfor, S. Bhattarachya, S. Lenhart, M. Martcheva, Optimal control in multi-group coupled within-host and between-host models. Electron. J. Differ. Equ. 23, 87–117 (2016)

    MathSciNet  MATH  Google Scholar 

  19. K.A. Pawelek, G.T. Huynh, M. Quinlivan, A. Cullinane, L. Rong, A.S. Perelson, Modeling within-host dynamics of influenza virus infection including immune responses. PLoS Comp. Biol. 8, e1002588 (2012)

    Article  MathSciNet  Google Scholar 

  20. H.R. Thieme, C. Castillo-Chavez, How may infection-age-dependent infectivity affect the dynamics of HIV/AIDS? SIAM J. Appl. Math. 53, 1447–1479 (1993)

    Article  MathSciNet  Google Scholar 

  21. N. Tuncer, M. Martcheva, Analytical and numerical approaches to coexistence of strains in a two-strain SIS model with diffusion. J. Biol. Dyn. 6, 406–439 (2012)

    Article  MathSciNet  Google Scholar 

  22. W. Wang, Y. Cai, M. Wu, K. Wang, Z. Li, Complex dynamics of a reaction-diffusion epidemic model. Nonlinear Anal. Real World Appl. 13, 2240–2258 (2012)

    Article  MathSciNet  Google Scholar 

  23. P.S. Wikramaratna, A. Kucharski, S. Gupta, V. Andreasen, A.R. McLean, J.R. Gog, Five challenges in modelling interacting strain dynamics. Epidemics 10, 31-4 (2014)

    Article  Google Scholar 

  24. D. Wodarz, Killer Cell Dynamics. Interdisciplinary Applied Mathematics, vol. 32 (Springer, New York, 2007). Mathematical and Computational Approaches to Immunology

    Google Scholar 

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Li, XZ., Yang, J., Martcheva, M. (2020). Nested Immuno-Epidemiological Models. In: Age Structured Epidemic Modeling. Interdisciplinary Applied Mathematics, vol 52. Springer, Cham. https://doi.org/10.1007/978-3-030-42496-1_3

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