Using process algebra to develop predator-prey models of within-host parasite dynamics

Chris McCaig, Andy Fenton, Andrea Linn Graham, Carron Shankland, Rachel Norman

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

As a first approximation of immune-mediated within-host parasite dynamics we can consider the immune response as a predator, with the parasite as its prey. In the ecological literature of predator-prey interactions there are a number of different functional responses used to describe how a predator reproduces in response to consuming prey. Until recently most of the models of the immune system that have taken a predator-prey approach have used simple mass action dynamics to capture the interaction between the immune response and the parasite. More recently Fenton and Perkins (2010) employed three of the most commonly used prey-dependent functional response terms from the ecological literature.In this paper we make use of a technique from computing science, process algebra, to develop mathematical models. The novelty of the process algebra approach is to allow stochastic models of the population (parasite and immune cells) to be developed from rules of individual cell behaviour. By using this approach in which individual cellular behaviour is captured we have derived a ratio-dependent response similar to that seen in the previous models of immune-mediated parasite dynamics, confirming that, whilst this type of term is controversial in ecological predator-prey models, it is appropriate for models of the immune system.

Original languageEnglish (US)
Pages (from-to)74-81
Number of pages8
JournalJournal of Theoretical Biology
Volume329
DOIs
StatePublished - Jul 1 2013

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

Keywords

  • Cellular interactions
  • Dynamics
  • Immune system
  • Mathematical models
  • Ratio dependence
  • WSCCS

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