title: Immune response to a variable pathogen: a stochastic model with two interlocked Darwinian entities.
abstract: This paper presents the modeling of a host immune system, more precisely the immune effector cell and immune memory cell population, and its interaction with an invading pathogen population. It will tackle two issues of interest; on the one hand, in defining a stochastic model accounting for the inherent nature of organisms in population dynamics, namely multiplication with mutation and selection; on the other hand, in providing a description of pathogens that may vary their antigens through mutations during infection of the host. Unlike most of the literature, which models the dynamics with first-order differential equations, this paper proposes a Galton-Watson type branching process to describe stochastically by whole distributions the population dynamics of pathogens and immune cells. In the first model case, the pathogen of a given type is either eradicated or shows oscillatory chronic response. In the second model case, the pathogen shows variational behavior changing its antigen resulting in a prolonged immune reaction.
authors: Biomedical Optics Research Laboratory, Clinic of Neonatology, University Hospital Zürich, Frauenklinikstrasse 10, CH-8091 Zürich, Switzerland. c-k@gmx.ch
authors: Christoph
authors: C
authors: Kuhn
mesh_terms: D000465:Algorithms; D000818:Animals; D005075:Biological Evolution; D006801:Humans; D007107:Immune System; D007239:Infections / Q000382:microbiology* / Q000469:parasitology* / Q000821:virology*; D008214:Lymphocytes / Q000276:immunology; D008490:Medical Informatics / Q000379:methods*; D018448:Models, Immunological; D015233:Models, Statistical; D011157:Population Dynamics; D011336:Probability; D013269:Stochastic Processes