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Modelling that shaped the early COVID-19 pandemic response in the UK
Infectious disease modelling has played an integral part of the scientific evidence used to guide the response to the COVID-19 pandemic. In the UK, modelling evidence used for policy is reported to the Scientific Advisory Group for Emergencies (SAGE) modelling subgroup, SPI-M-O (Scientific Pandemic...
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/PMC8165593/ https://www.ncbi.nlm.nih.gov/pubmed/34053252 http://dx.doi.org/10.1098/rstb.2021.0001 |
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author | Brooks-Pollock, Ellen Danon, Leon Jombart, Thibaut Pellis, Lorenzo |
author_facet | Brooks-Pollock, Ellen Danon, Leon Jombart, Thibaut Pellis, Lorenzo |
author_sort | Brooks-Pollock, Ellen |
collection | PubMed |
description | Infectious disease modelling has played an integral part of the scientific evidence used to guide the response to the COVID-19 pandemic. In the UK, modelling evidence used for policy is reported to the Scientific Advisory Group for Emergencies (SAGE) modelling subgroup, SPI-M-O (Scientific Pandemic Influenza Group on Modelling-Operational). This Special Issue contains 20 articles detailing evidence that underpinned advice to the UK government during the SARS-CoV-2 pandemic in the UK between January 2020 and July 2020. Here, we introduce the UK scientific advisory system and how it operates in practice, and discuss how infectious disease modelling can be useful in policy making. We examine the drawbacks of current publishing practices and academic credit and highlight the importance of transparency and reproducibility during an epidemic emergency. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’. |
format | Online Article Text |
id | pubmed-8165593 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-81655932021-06-03 Modelling that shaped the early COVID-19 pandemic response in the UK Brooks-Pollock, Ellen Danon, Leon Jombart, Thibaut Pellis, Lorenzo Philos Trans R Soc Lond B Biol Sci Introduction Infectious disease modelling has played an integral part of the scientific evidence used to guide the response to the COVID-19 pandemic. In the UK, modelling evidence used for policy is reported to the Scientific Advisory Group for Emergencies (SAGE) modelling subgroup, SPI-M-O (Scientific Pandemic Influenza Group on Modelling-Operational). This Special Issue contains 20 articles detailing evidence that underpinned advice to the UK government during the SARS-CoV-2 pandemic in the UK between January 2020 and July 2020. Here, we introduce the UK scientific advisory system and how it operates in practice, and discuss how infectious disease modelling can be useful in policy making. We examine the drawbacks of current publishing practices and academic credit and highlight the importance of transparency and reproducibility during an epidemic emergency. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’. The Royal Society 2021-07-19 2021-05-31 /pmc/articles/PMC8165593/ /pubmed/34053252 http://dx.doi.org/10.1098/rstb.2021.0001 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 | Introduction Brooks-Pollock, Ellen Danon, Leon Jombart, Thibaut Pellis, Lorenzo Modelling that shaped the early COVID-19 pandemic response in the UK |
title | Modelling that shaped the early COVID-19 pandemic response in the UK |
title_full | Modelling that shaped the early COVID-19 pandemic response in the UK |
title_fullStr | Modelling that shaped the early COVID-19 pandemic response in the UK |
title_full_unstemmed | Modelling that shaped the early COVID-19 pandemic response in the UK |
title_short | Modelling that shaped the early COVID-19 pandemic response in the UK |
title_sort | modelling that shaped the early covid-19 pandemic response in the uk |
topic | Introduction |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165593/ https://www.ncbi.nlm.nih.gov/pubmed/34053252 http://dx.doi.org/10.1098/rstb.2021.0001 |
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