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

Citation

McCaig 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/s12064-010-0106-8

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

Keywords
epidemiology; multiscale modelling; theoretical computer science; changing scale; Communicable diseases Mathematical models; Population biology Mathematical models

Journal
Theory in Biosciences: Volume 130, Issue 1

People

Professor Rachel Norman

Chair in Food Security & Sustainability, Mathematics