From individuals to populations : a symbolic process algebra approach to epidemiology.
McCaig, Chris and Norman, R. and Shankland, C. (2009) From individuals to populations : a symbolic process algebra approach to epidemiology. Mathematics in Computer Science, 2 (3). pp. 535-556. ISSN 1661-8270 (https://doi.org/10.1007/s11786-008-0066-2)
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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.
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Item type: Article ID code: 46389 Dates: DateEvent1 March 2009PublishedSubjects: Science > Mathematics > Probabilities. Mathematical statistics Department: Faculty of Science > Mathematics and Statistics Depositing user: Pure Administrator Date deposited: 06 Jan 2014 15:45 Last modified: 08 Apr 2024 20:55 URI: https://strathprints.strath.ac.uk/id/eprint/46389