Literature DB >> 20809367

A rigorous approach to investigating common assumptions about disease transmission: Process algebra as an emerging modelling methodology for epidemiology.

Chris McCaig1, Mike Begon, Rachel Norman, Carron Shankland.   

Abstract

Changing scale, for example, the ability to move seamlessly from an individual-based model to a population-based model, is an important problem in many fields. In this paper, we introduce process algebra as a novel solution to this problem in the context of models of infectious disease spread. Process algebra allows us to describe a system in terms of the stochastic behaviour of individuals, and is a technique from computer science. We review the use of process algebra in biological systems, and the variety of quantitative and qualitative analysis techniques available. The analysis illustrated here solves the changing scale problem: from the individual behaviour we can rigorously derive equations to describe the mean behaviour of the system at the level of the population. The biological problem investigated is the transmission of infection, and how this relates to individual interactions.

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Year:  2010        PMID: 20809367     DOI: 10.1007/s12064-010-0106-8

Source DB:  PubMed          Journal:  Theory Biosci        ISSN: 1431-7613            Impact factor:   1.919


  14 in total

1.  Representation and simulation of biochemical processes using the pi-calculus process algebra.

Authors:  A Regev; W Silverman; E Shapiro
Journal:  Pac Symp Biocomput       Date:  2001

2.  Pair approximation for lattice models with multiple interaction scales.

Authors:  S P Ellner
Journal:  J Theor Biol       Date:  2001-06-21       Impact factor: 2.691

3.  Relating individual behaviour to population dynamics.

Authors:  D J Sumpter; D S Broomhead
Journal:  Proc Biol Sci       Date:  2001-05-07       Impact factor: 5.349

4.  Modelling pathogen transmission: the interrelationship between local and global approaches.

Authors:  Joanne Turner; Michael Begon; Roger G Bowers
Journal:  Proc Biol Sci       Date:  2003-01-07       Impact factor: 5.349

5.  A clarification of transmission terms in host-microparasite models: numbers, densities and areas.

Authors:  M Begon; M Bennett; R G Bowers; N P French; S M Hazel; J Turner
Journal:  Epidemiol Infect       Date:  2002-08       Impact factor: 2.451

6.  Stochastic and spatial dynamics of nematode parasites in farmed ruminants.

Authors:  Stephen J Cornell; Valerie S Isham; Bryan T Grenfell
Journal:  Proc Biol Sci       Date:  2004-06-22       Impact factor: 5.349

7.  Spatially extended host-parasite interactions: the role of recovery and immunity.

Authors:  Steven D Webb; Matt J Keeling; Mike Boots
Journal:  Theor Popul Biol       Date:  2006-09-22       Impact factor: 1.570

8.  Parasite-driven extinction in spatially explicit host-parasite systems.

Authors:  Michael Boots; Akira Sasaki
Journal:  Am Nat       Date:  2002-06       Impact factor: 3.926

9.  Contact rate calculation for a basic epidemic model.

Authors:  C J Rhodes; R M Anderson
Journal:  Math Biosci       Date:  2008-11       Impact factor: 2.144

10.  Host-parasite interactions between the local and the mean-field: how and when does spatial population structure matter?

Authors:  Steven D Webb; Matt J Keeling; Mike Boots
Journal:  J Theor Biol       Date:  2007-06-16       Impact factor: 2.691

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  1 in total

1.  Emerging modelling methodologies in medicine and biology, Introduction to the special issue.

Authors:  Jamie Davies; Michael Grinfeld; Steven D Webb
Journal:  Theory Biosci       Date:  2011-03       Impact factor: 1.919

  1 in total

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