A baseline metapopulation model for the competition between microparasites and host immune response

Immunological memory is clearly an important topic in any consideration of the interaction between host and parasite, both at the individual and at the population level. However, whether such immunity is maintained via constant exposure to infection via long-lived clones of lymphocytes that are able to recognize specific antigens and maintain antibody production in the absence of repeated exposure, or via the persistence of the microparasite at low levels of abundance within the host such that antibodies are constantly produced, remains unclair at present. Moreover, recent theoretical work suggest that immunological memory may be a dynamic state arising either from regulatory networks within the immune system, or from the continual persistence of the infectious agent within the host. A model is described as a baseline model when it addresses only the most fundamental aspects of the behaviour in question. Thus in the present context the baseline metapopulation model (spatially explicit model) focuses on the dynamics interaction between a population of microparasites within a host and the immune system of the host. The behaviour of the baseline model provides a firm background against which the microscopic dynamics of the underlying parasite organisms can be studied. We address this issue by develop a probabilistic cellular automata model for the competition between a population of effector cells (such as T and B lymphocytes which specifically recognize viral antigens) and a population of microparasites (that those entities within the host immune system, act to restrict its growth). This is a clearly a gross oversimplification of the many cell types and chemical factors involved in an immune response and their action in producing the specific antibodies that help to kill the microparasites. Moreover, in this scenario we consider two different approaches to the description of the interaction: namely on based on an antigen-driven view of the immune system and the other based on the network regulation of interactions between different (two) cell types within the immune system and the replicatin antigen. Finally, base on the previous approaches we consider futher that the two populations (microparasites and immune response cells) can move randomly (diffuse) on a twodimensional surface and the competition (replicate and interact) mimic the predator-prey interaction between these two species, on a spatial domain. (Financial support: FAPESP, Proc. 02/03564-8 and 02/08802-4). (Subject Topic: Complexity, Dynamical Systems) REFERENCES[1]Anderson R. M. and May R. M., Infectious Diseases ofHumans (Oxford University Press, Oxford, 1991). [2]Arnaout, R. A., and Nowak, M., Competitive Coexistence inAntiviral Immunity, J. Theor. Biol., 204, 431 (2000). [3]Alves, D., Hass V. and Caliri, A. The predictive power of R0in an epidemic probabilistic model, Journal of BiologicalPhysics , vol. 29, issue 1 (2003). [4]Alves, D. and Fontanari, J.F., Error threshold in finitepopulations, Phys. Rev. E, 57, 7008, june, (1998). [5]Kamp, C. and Bornholdt, S., Co-Evolution of quasispecies: B-cell mutation rates maximize viral error catastrophes,Preprint cond-mat/0108353. [6]Alves, D. and Caliri, A. Epidemic propagation model and theevolution of antibiotic resistance, European Journal ofPharmaceutical Sciences, vol. 13, suppl. 1, s125, 2001.