Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/3111
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dc.contributor.authorMcCaig, Chrisen_UK
dc.contributor.authorBegon, Mikeen_UK
dc.contributor.authorNorman, Rachelen_UK
dc.contributor.authorShankland, Carronen_UK
dc.date.accessioned2016-11-12T00:16:29Z-
dc.date.available2016-11-12T00:16:29Z-
dc.date.issued2011-03en_UK
dc.identifier.urihttp://hdl.handle.net/1893/3111-
dc.description.abstractChanging 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 interactionsen_UK
dc.language.isoenen_UK
dc.publisherSpringeren_UK
dc.relationMcCaig C, Begon M, Norman R & Shankland C (2011) A rigorous approach to investigating common assumptions about disease transmission: Process algebra as an emerging modelling methodology for epidemiology. Theory in Biosciences, 130 (1), pp. 19-29. http://www.springerlink.com/content/1431-7613/; https://doi.org/10.1007/s12064-010-0106-8en_UK
dc.rightsPublished in Theory in Biosciences by Springer.; The final publication is available at www.springerlink.com. http://www.springerlink.com/content/9t33247x507v4378/en_UK
dc.subjectepidemiologyen_UK
dc.subjectmultiscale modellingen_UK
dc.subjecttheoretical computer scienceen_UK
dc.subjectchanging scaleen_UK
dc.subjectCommunicable diseases Mathematical modelsen_UK
dc.subjectPopulation biology Mathematical modelsen_UK
dc.titleA rigorous approach to investigating common assumptions about disease transmission: Process algebra as an emerging modelling methodology for epidemiologyen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1007/s12064-010-0106-8en_UK
dc.citation.jtitleTheorie in den Biowissenschaften / Theory in Biosciencesen_UK
dc.citation.issn1611-7530en_UK
dc.citation.issn1431-7613en_UK
dc.citation.volume130en_UK
dc.citation.issue1en_UK
dc.citation.spage19en_UK
dc.citation.epage29en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.identifier.urlhttp://www.springerlink.com/content/1431-7613/en_UK
dc.author.emailran@maths.stir.ac.uken_UK
dc.contributor.affiliationUniversity of Stirlingen_UK
dc.contributor.affiliationUniversity of Liverpoolen_UK
dc.contributor.affiliationMathematicsen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.identifier.isiWOS:000290934500003en_UK
dc.identifier.scopusid2-s2.0-79952193050en_UK
dc.identifier.wtid829696en_UK
dc.contributor.orcid0000-0002-7398-6064en_UK
dc.contributor.orcid0000-0001-7672-2884en_UK
dc.date.accepted2010-07-04en_UK
dc.date.filedepositdate2011-06-23en_UK
Appears in Collections:Computing Science and Mathematics Journal Articles

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