Please use this identifier to cite or link to this item:
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: From Individuals to Populations: A Symbolic Process Algebra Approach to Epidemiology
Author(s): McCaig, Chris
Norman, Rachel
Shankland, Carron
Contact Email:
Keywords: Process Algebra
Population Dynamics
Mean Field
Symbolic Computation
Epidemiology Methodology
Issue Date: Mar-2009
Date Deposited: 29-Jun-2011
Citation: McCaig C, Norman R & Shankland C (2009) From Individuals to Populations: A Symbolic Process Algebra Approach to Epidemiology. Mathematics in Computer Science, 2 (3), pp. 535-556.;
Abstract: Is it possible to symbolically express and analyse an individual-based model of disease spread, including realistic population dynamics? This problem is addressed through the use of process algebra and a novel method for transforming process algebra into Mean Field Equations. A number of stochastic models of population growth are presented, exploring different representations based on alternative views of individual behaviour. The overall population dynamics in terms of mean field equations are derived using a formal and rigorous rewriting based method. These equations are easily compared with the traditionally used deterministic Ordinary Differential Equation models and allow evaluation of those ODE models, challenging their assumptions about system dynamics. The utility of our approach for epidemiology is confirmed by constructing a model combining population growth with disease spread and fitting it to data on HIV in the UK population.
DOI Link: 10.1007/s11786-008-0066-2
Rights: Published in Mathematics in Computer Science by Springer.; The final publication is available at

Files in This Item:
File Description SizeFormat 
MCS.pdfFulltext - Accepted Version262.41 kBAdobe PDFView/Open

This item is protected by original copyright

Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved

If you believe that any material held in STORRE infringes copyright, please contact providing details and we will remove the Work from public display in STORRE and investigate your claim.