The research and development process for multiscale models of infectious disease systems.

Multiscale modelling of infectious disease systems falls within the domain of complexity science-the study of complex systems. However, what should be made clear is that current progress in multiscale modelling of infectious disease dynamics is still as yet insufficient to present it as a mature sub...

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Main Author: Winston Garira
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-04-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1007734
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spelling doaj-327ed1ae31574b4d9813a002dfb8313f2021-04-21T15:15:03ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582020-04-01164e100773410.1371/journal.pcbi.1007734The research and development process for multiscale models of infectious disease systems.Winston GariraMultiscale modelling of infectious disease systems falls within the domain of complexity science-the study of complex systems. However, what should be made clear is that current progress in multiscale modelling of infectious disease dynamics is still as yet insufficient to present it as a mature sub-discipline of complexity science. In this article we present a methodology for development of multiscale models of infectious disease systems. This methodology is a set of partially ordered research and development activities that result in multiscale models of infectious disease systems built from different scientific approaches. Therefore, the conclusive result of this article is a methodology to design multiscale models of infectious diseases. Although this research and development process for multiscale models cannot be claimed to be unique and final, it constitutes a good starting point, which may be found useful as a basis for further refinement in the discourse for multiscale modelling of infectious disease dynamics.https://doi.org/10.1371/journal.pcbi.1007734
collection DOAJ
language English
format Article
sources DOAJ
author Winston Garira
spellingShingle Winston Garira
The research and development process for multiscale models of infectious disease systems.
PLoS Computational Biology
author_facet Winston Garira
author_sort Winston Garira
title The research and development process for multiscale models of infectious disease systems.
title_short The research and development process for multiscale models of infectious disease systems.
title_full The research and development process for multiscale models of infectious disease systems.
title_fullStr The research and development process for multiscale models of infectious disease systems.
title_full_unstemmed The research and development process for multiscale models of infectious disease systems.
title_sort research and development process for multiscale models of infectious disease systems.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2020-04-01
description Multiscale modelling of infectious disease systems falls within the domain of complexity science-the study of complex systems. However, what should be made clear is that current progress in multiscale modelling of infectious disease dynamics is still as yet insufficient to present it as a mature sub-discipline of complexity science. In this article we present a methodology for development of multiscale models of infectious disease systems. This methodology is a set of partially ordered research and development activities that result in multiscale models of infectious disease systems built from different scientific approaches. Therefore, the conclusive result of this article is a methodology to design multiscale models of infectious diseases. Although this research and development process for multiscale models cannot be claimed to be unique and final, it constitutes a good starting point, which may be found useful as a basis for further refinement in the discourse for multiscale modelling of infectious disease dynamics.
url https://doi.org/10.1371/journal.pcbi.1007734
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