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June: open-source individual-based epidemiology simulation
We introduce June, an open-source framework for the detailed simulation of epidemics on the basis of social interactions in a virtual population constructed from geographically granular census data, reflecting age, sex, ethnicity and socio-economic indicators. Interactions between individuals are mo...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8261230/ https://www.ncbi.nlm.nih.gov/pubmed/34295529 http://dx.doi.org/10.1098/rsos.210506 |
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author | Aylett-Bullock, Joseph Cuesta-Lazaro, Carolina Quera-Bofarull, Arnau Icaza-Lizaola, Miguel Sedgewick, Aidan Truong, Henry Curran, Aoife Elliott, Edward Caulfield, Tristan Fong, Kevin Vernon, Ian Williams, Julian Bower, Richard Krauss, Frank |
author_facet | Aylett-Bullock, Joseph Cuesta-Lazaro, Carolina Quera-Bofarull, Arnau Icaza-Lizaola, Miguel Sedgewick, Aidan Truong, Henry Curran, Aoife Elliott, Edward Caulfield, Tristan Fong, Kevin Vernon, Ian Williams, Julian Bower, Richard Krauss, Frank |
author_sort | Aylett-Bullock, Joseph |
collection | PubMed |
description | We introduce June, an open-source framework for the detailed simulation of epidemics on the basis of social interactions in a virtual population constructed from geographically granular census data, reflecting age, sex, ethnicity and socio-economic indicators. Interactions between individuals are modelled in groups of various sizes and properties, such as households, schools and workplaces, and other social activities using social mixing matrices. June provides a suite of flexible parametrizations that describe infectious diseases, how they are transmitted and affect contaminated individuals. In this paper, we apply June to the specific case of modelling the spread of COVID-19 in England. We discuss the quality of initial model outputs which reproduce reported hospital admission and mortality statistics at national and regional levels as well as by age strata. |
format | Online Article Text |
id | pubmed-8261230 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-82612302021-07-21 June: open-source individual-based epidemiology simulation Aylett-Bullock, Joseph Cuesta-Lazaro, Carolina Quera-Bofarull, Arnau Icaza-Lizaola, Miguel Sedgewick, Aidan Truong, Henry Curran, Aoife Elliott, Edward Caulfield, Tristan Fong, Kevin Vernon, Ian Williams, Julian Bower, Richard Krauss, Frank R Soc Open Sci Mathematics We introduce June, an open-source framework for the detailed simulation of epidemics on the basis of social interactions in a virtual population constructed from geographically granular census data, reflecting age, sex, ethnicity and socio-economic indicators. Interactions between individuals are modelled in groups of various sizes and properties, such as households, schools and workplaces, and other social activities using social mixing matrices. June provides a suite of flexible parametrizations that describe infectious diseases, how they are transmitted and affect contaminated individuals. In this paper, we apply June to the specific case of modelling the spread of COVID-19 in England. We discuss the quality of initial model outputs which reproduce reported hospital admission and mortality statistics at national and regional levels as well as by age strata. The Royal Society 2021-07-07 /pmc/articles/PMC8261230/ /pubmed/34295529 http://dx.doi.org/10.1098/rsos.210506 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Mathematics Aylett-Bullock, Joseph Cuesta-Lazaro, Carolina Quera-Bofarull, Arnau Icaza-Lizaola, Miguel Sedgewick, Aidan Truong, Henry Curran, Aoife Elliott, Edward Caulfield, Tristan Fong, Kevin Vernon, Ian Williams, Julian Bower, Richard Krauss, Frank June: open-source individual-based epidemiology simulation |
title | June: open-source individual-based epidemiology simulation |
title_full | June: open-source individual-based epidemiology simulation |
title_fullStr | June: open-source individual-based epidemiology simulation |
title_full_unstemmed | June: open-source individual-based epidemiology simulation |
title_short | June: open-source individual-based epidemiology simulation |
title_sort | june: open-source individual-based epidemiology simulation |
topic | Mathematics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8261230/ https://www.ncbi.nlm.nih.gov/pubmed/34295529 http://dx.doi.org/10.1098/rsos.210506 |
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