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Disease transmission and control modelling at the science–policy interface
The coronavirus disease 2019 (COVID-19) pandemic has disrupted the lives of billions across the world. Mathematical modelling has been a key tool deployed throughout the pandemic to explore the potential public health impact of an unmitigated epidemic. The results of such studies have informed gover...
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/PMC8504885/ https://www.ncbi.nlm.nih.gov/pubmed/34956589 http://dx.doi.org/10.1098/rsfs.2021.0013 |
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author | McCabe, Ruth Donnelly, Christl A. |
author_facet | McCabe, Ruth Donnelly, Christl A. |
author_sort | McCabe, Ruth |
collection | PubMed |
description | The coronavirus disease 2019 (COVID-19) pandemic has disrupted the lives of billions across the world. Mathematical modelling has been a key tool deployed throughout the pandemic to explore the potential public health impact of an unmitigated epidemic. The results of such studies have informed governments' decisions to implement non-pharmaceutical interventions to control the spread of the virus. In this article, we explore the complex relationships between models, decision-making, the media and the public during the COVID-19 pandemic in the United Kingdom of Great Britain and Northern Ireland (UK). Doing so not only provides an important historical context of COVID-19 modelling and how it has shaped the UK response, but as the pandemic continues and looking towards future pandemic preparedness, understanding these relationships and how they might be improved is critical. As such, we have synthesized information gathered via three methods: a survey to publicly list attendees of the Scientific Advisory Group for Emergencies, the Scientific Pandemic Influenza Group on Modelling and other comparable advisory bodies, interviews with science communication experts and former scientific advisors, and reviewing some of the key COVID-19 modelling literature from 2020. Our research highlights the desire for increased bidirectional communication between modellers, decision-makers and the public, as well as the need to convey uncertainty inherent in transmission models in a clear manner. These aspects should be considered carefully ahead of the next emergency response. |
format | Online Article Text |
id | pubmed-8504885 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-85048852022-02-02 Disease transmission and control modelling at the science–policy interface McCabe, Ruth Donnelly, Christl A. Interface Focus Articles The coronavirus disease 2019 (COVID-19) pandemic has disrupted the lives of billions across the world. Mathematical modelling has been a key tool deployed throughout the pandemic to explore the potential public health impact of an unmitigated epidemic. The results of such studies have informed governments' decisions to implement non-pharmaceutical interventions to control the spread of the virus. In this article, we explore the complex relationships between models, decision-making, the media and the public during the COVID-19 pandemic in the United Kingdom of Great Britain and Northern Ireland (UK). Doing so not only provides an important historical context of COVID-19 modelling and how it has shaped the UK response, but as the pandemic continues and looking towards future pandemic preparedness, understanding these relationships and how they might be improved is critical. As such, we have synthesized information gathered via three methods: a survey to publicly list attendees of the Scientific Advisory Group for Emergencies, the Scientific Pandemic Influenza Group on Modelling and other comparable advisory bodies, interviews with science communication experts and former scientific advisors, and reviewing some of the key COVID-19 modelling literature from 2020. Our research highlights the desire for increased bidirectional communication between modellers, decision-makers and the public, as well as the need to convey uncertainty inherent in transmission models in a clear manner. These aspects should be considered carefully ahead of the next emergency response. The Royal Society 2021-10-12 /pmc/articles/PMC8504885/ /pubmed/34956589 http://dx.doi.org/10.1098/rsfs.2021.0013 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 | Articles McCabe, Ruth Donnelly, Christl A. Disease transmission and control modelling at the science–policy interface |
title | Disease transmission and control modelling at the science–policy interface |
title_full | Disease transmission and control modelling at the science–policy interface |
title_fullStr | Disease transmission and control modelling at the science–policy interface |
title_full_unstemmed | Disease transmission and control modelling at the science–policy interface |
title_short | Disease transmission and control modelling at the science–policy interface |
title_sort | disease transmission and control modelling at the science–policy interface |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504885/ https://www.ncbi.nlm.nih.gov/pubmed/34956589 http://dx.doi.org/10.1098/rsfs.2021.0013 |
work_keys_str_mv | AT mccaberuth diseasetransmissionandcontrolmodellingatthesciencepolicyinterface AT donnellychristla diseasetransmissionandcontrolmodellingatthesciencepolicyinterface |