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An extensible spatial and temporal epidemiological modelling system
BACKGROUND: This paper describes the Spatiotemporal Epidemiological Modeller (STEM) which is an extensible software system and framework for modelling the spatial and temporal progression of multiple diseases affecting multiple populations in geographically distributed locations. STEM is an experime...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2006
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1360062/ https://www.ncbi.nlm.nih.gov/pubmed/16417637 http://dx.doi.org/10.1186/1476-072X-5-4 |
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author | Ford, Daniel Alexander Kaufman, James H Eiron, Iris |
author_facet | Ford, Daniel Alexander Kaufman, James H Eiron, Iris |
author_sort | Ford, Daniel Alexander |
collection | PubMed |
description | BACKGROUND: This paper describes the Spatiotemporal Epidemiological Modeller (STEM) which is an extensible software system and framework for modelling the spatial and temporal progression of multiple diseases affecting multiple populations in geographically distributed locations. STEM is an experiment in developing a software system that can model complex epidemiological scenarios while also being extensible by the research community. The ultimate goal of STEM is to provide a common modelling platform powerful enough to be sufficient for all modelling scenarios and extensible in a way that allows different researchers to combine their efforts in developing exceptionally good models. RESULTS: STEM is a powerful modelling system that allows researchers to model scenarios with unmixed populations that are not uniformly distributed and in which multiple populations exist that are being infected with multiple diseases. It's underlying representational framework, a graph, and its software architecture allow the system to be extended by incorporating software components developed by different researchers. CONCLUSION: This approach taken in the design of STEM creates a powerful platform for epidemiological research collaboration. Future versions of the system will make such collaborative efforts easy and common. |
format | Text |
id | pubmed-1360062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-13600622006-02-02 An extensible spatial and temporal epidemiological modelling system Ford, Daniel Alexander Kaufman, James H Eiron, Iris Int J Health Geogr Methodology BACKGROUND: This paper describes the Spatiotemporal Epidemiological Modeller (STEM) which is an extensible software system and framework for modelling the spatial and temporal progression of multiple diseases affecting multiple populations in geographically distributed locations. STEM is an experiment in developing a software system that can model complex epidemiological scenarios while also being extensible by the research community. The ultimate goal of STEM is to provide a common modelling platform powerful enough to be sufficient for all modelling scenarios and extensible in a way that allows different researchers to combine their efforts in developing exceptionally good models. RESULTS: STEM is a powerful modelling system that allows researchers to model scenarios with unmixed populations that are not uniformly distributed and in which multiple populations exist that are being infected with multiple diseases. It's underlying representational framework, a graph, and its software architecture allow the system to be extended by incorporating software components developed by different researchers. CONCLUSION: This approach taken in the design of STEM creates a powerful platform for epidemiological research collaboration. Future versions of the system will make such collaborative efforts easy and common. BioMed Central 2006-01-17 /pmc/articles/PMC1360062/ /pubmed/16417637 http://dx.doi.org/10.1186/1476-072X-5-4 Text en Copyright © 2006 Ford et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Ford, Daniel Alexander Kaufman, James H Eiron, Iris An extensible spatial and temporal epidemiological modelling system |
title | An extensible spatial and temporal epidemiological modelling system |
title_full | An extensible spatial and temporal epidemiological modelling system |
title_fullStr | An extensible spatial and temporal epidemiological modelling system |
title_full_unstemmed | An extensible spatial and temporal epidemiological modelling system |
title_short | An extensible spatial and temporal epidemiological modelling system |
title_sort | extensible spatial and temporal epidemiological modelling system |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1360062/ https://www.ncbi.nlm.nih.gov/pubmed/16417637 http://dx.doi.org/10.1186/1476-072X-5-4 |
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