title: Probing the effects of the well-mixed assumption on viral infection dynamics.
abstract: Viral kinetics have been extensively studied in the past through the use of spatially well-mixed ordinary differential equations describing the time evolution of the diseased state. However, emerging spatial structures such as localized populations of dead cells might adversely affect the spread of infection, similar to the manner in which a counter-fire can stop a forest fire from spreading. In a previous publication [Beauchemin, C., Samuel, J., Tuszynski, J., 2005. A simple cellular automaton model for influenza A viral infections. J. Theor. Biol. 232(2), 223-234], a simple two-dimensional cellular automaton model was introduced and shown to be accurate enough to model an uncomplicated infection with influenza A. Here, this model is used to investigate the effects of relaxing the well-mixed assumption. Particularly, the effects of the initial distribution of infected cells, the regeneration rule for dead epithelial cells, and the proliferation rule for immune cells are explored and shown to have an important impact on the development and outcome of the viral infection in our model.
authors.affiliation: Department of Physics, University of Alberta, Edmonton, AB, Canada T6G 2J1. cbeau@cs.unm.edu <cbeau@cs.unm.edu>
authors.forename: Catherine
authors.initials: C
authors.lastname: Beauchemin
mesh_terms: D000818:Animals; D049109:Cell Proliferation; D002908:Chronic Disease; D004847:Epithelial Cells / Q000502:physiology / Q000821:virology; D006801:Humans; D007111:Immunity, Cellular; D009980:Influenza A virus / Q000502:physiology; D007251:Influenza, Human / Q000473:pathology; D008954:Models, Biological; D012038:Regeneration; D014777:Virus Diseases / Q000276:immunology / Q000473:pathology*