Persistent infections are a major problem for human health. In recent years, much progress has been made in understanding the molecular and cellular biology of pathogens (viruses, bacteria, and protozoa) that cause acute infections and the changes in the phenotype of the immune cells responding to these pathogens [1-3]. Much less is known for persistent infections. While understanding the underlying molecular and cellular biology is important, and even critical, it is not sufficient for predicting the overall system's behavior as virus interaction with the immune system is highly dynamic. Responses involve exponential increases in populations of the pathogen and specific immune cells responding against it, together with differentiation of the immune cell phenotypes over time. Understanding persistent infections will thus require incorporating the main features of the biology of pathogen and immune cells into dynamical models that describe the changes in these populations over time [4, 5]. In this chapter, we review the contribution of mathematical models to our understanding of the dynamics of immune exhaustion during persistent infections with a focus on the dynamics of CD8 T cells and immunopathology.
|Original language||English (US)|
|Title of host publication||Mathematical, Computational and Experimental T Cell Immunology|
|Publisher||Springer International Publishing|
|Number of pages||12|
|State||Published - Jan 4 2021|
ASJC Scopus subject areas
- Immunology and Microbiology(all)