A rigorous approach to investigating common assumptions about disease transmission: Process algebra as an emerging modelling methodology for epidemiology
| Autor: | Rachel Norman, Chris McCaig, Carron Shankland, Michael Begon |
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| Rok vydání: | 2009 |
| Předmět: |
Statistics and Probability
Theoretical computer science Computer science Process calculus Population Complex system Communicable diseases Mathematical models Communicable Diseases Models Biological Disease Outbreaks Qualitative analysis theoretical computer science Humans Computer Simulation education Ecology Evolution Behavior and Systematics education.field_of_study Stochastic Processes Applied Mathematics changing scale Markov Chains Philosophy of biology Biological Problem epidemiology multiscale modelling Disease transmission Population biology Mathematical models |
| Zdroj: | Theory in biosciences = Theorie in den Biowissenschaften. 130(1) |
| ISSN: | 1611-7530 1431-7613 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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