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Getting the most out of maths: How to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the COVID-19 response in the UK

In March 2020 mathematics became a key part of the scientific advice to the UK government on the pandemic response to COVID-19. Mathematical and statistical modelling provided critical information on the spread of the virus and the potential impact of different interventions. The unprecedented scale...

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Autores principales: Dangerfield, Ciara E., David Abrahams, I., Budd, Chris, Butchers, Matt, Cates, Michael E., Champneys, Alan R., Currie, Christine S.M., Enright, Jessica, Gog, Julia R., Goriely, Alain, Déirdre Hollingsworth, T., Hoyle, Rebecca B., INI Professional Services, Isham, Valerie, Jordan, Joanna, Kaouri, Maha H., Kavoussanakis, Kostas, Leeks, Jane, Maini, Philip K., Marr, Christie, Merritt, Clare, Mollison, Denis, Ray, Surajit, Thompson, Robin N., Wakefield, Alexandra, Wasley, Dawn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier Ltd. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9618296/
https://www.ncbi.nlm.nih.gov/pubmed/36323393
http://dx.doi.org/10.1016/j.jtbi.2022.111332
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author Dangerfield, Ciara E.
David Abrahams, I.
Budd, Chris
Butchers, Matt
Cates, Michael E.
Champneys, Alan R.
Currie, Christine S.M.
Enright, Jessica
Gog, Julia R.
Goriely, Alain
Déirdre Hollingsworth, T.
Hoyle, Rebecca B.
INI Professional Services
Isham, Valerie
Jordan, Joanna
Kaouri, Maha H.
Kavoussanakis, Kostas
Leeks, Jane
Maini, Philip K.
Marr, Christie
Merritt, Clare
Mollison, Denis
Ray, Surajit
Thompson, Robin N.
Wakefield, Alexandra
Wasley, Dawn
author_facet Dangerfield, Ciara E.
David Abrahams, I.
Budd, Chris
Butchers, Matt
Cates, Michael E.
Champneys, Alan R.
Currie, Christine S.M.
Enright, Jessica
Gog, Julia R.
Goriely, Alain
Déirdre Hollingsworth, T.
Hoyle, Rebecca B.
INI Professional Services
Isham, Valerie
Jordan, Joanna
Kaouri, Maha H.
Kavoussanakis, Kostas
Leeks, Jane
Maini, Philip K.
Marr, Christie
Merritt, Clare
Mollison, Denis
Ray, Surajit
Thompson, Robin N.
Wakefield, Alexandra
Wasley, Dawn
author_sort Dangerfield, Ciara E.
collection PubMed
description In March 2020 mathematics became a key part of the scientific advice to the UK government on the pandemic response to COVID-19. Mathematical and statistical modelling provided critical information on the spread of the virus and the potential impact of different interventions. The unprecedented scale of the challenge led the epidemiological modelling community in the UK to be pushed to its limits. At the same time, mathematical modellers across the country were keen to use their knowledge and skills to support the COVID-19 modelling effort. However, this sudden great interest in epidemiological modelling needed to be coordinated to provide much-needed support, and to limit the burden on epidemiological modellers already very stretched for time. In this paper we describe three initiatives set up in the UK in spring 2020 to coordinate the mathematical sciences research community in supporting mathematical modelling of COVID-19. Each initiative had different primary aims and worked to maximise synergies between the various projects. We reflect on the lessons learnt, highlighting the key roles of pre-existing research collaborations and focal centres of coordination in contributing to the success of these initiatives. We conclude with recommendations about important ways in which the scientific research community could be better prepared for future pandemics. This manuscript was submitted as part of a theme issue on “Modelling COVID-19 and Preparedness for Future Pandemics”.
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spelling pubmed-96182962022-10-31 Getting the most out of maths: How to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the COVID-19 response in the UK Dangerfield, Ciara E. David Abrahams, I. Budd, Chris Butchers, Matt Cates, Michael E. Champneys, Alan R. Currie, Christine S.M. Enright, Jessica Gog, Julia R. Goriely, Alain Déirdre Hollingsworth, T. Hoyle, Rebecca B. INI Professional Services Isham, Valerie Jordan, Joanna Kaouri, Maha H. Kavoussanakis, Kostas Leeks, Jane Maini, Philip K. Marr, Christie Merritt, Clare Mollison, Denis Ray, Surajit Thompson, Robin N. Wakefield, Alexandra Wasley, Dawn J Theor Biol Article In March 2020 mathematics became a key part of the scientific advice to the UK government on the pandemic response to COVID-19. Mathematical and statistical modelling provided critical information on the spread of the virus and the potential impact of different interventions. The unprecedented scale of the challenge led the epidemiological modelling community in the UK to be pushed to its limits. At the same time, mathematical modellers across the country were keen to use their knowledge and skills to support the COVID-19 modelling effort. However, this sudden great interest in epidemiological modelling needed to be coordinated to provide much-needed support, and to limit the burden on epidemiological modellers already very stretched for time. In this paper we describe three initiatives set up in the UK in spring 2020 to coordinate the mathematical sciences research community in supporting mathematical modelling of COVID-19. Each initiative had different primary aims and worked to maximise synergies between the various projects. We reflect on the lessons learnt, highlighting the key roles of pre-existing research collaborations and focal centres of coordination in contributing to the success of these initiatives. We conclude with recommendations about important ways in which the scientific research community could be better prepared for future pandemics. This manuscript was submitted as part of a theme issue on “Modelling COVID-19 and Preparedness for Future Pandemics”. The Author(s). Published by Elsevier Ltd. 2023-01-21 2022-10-30 /pmc/articles/PMC9618296/ /pubmed/36323393 http://dx.doi.org/10.1016/j.jtbi.2022.111332 Text en © 2022 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Dangerfield, Ciara E.
David Abrahams, I.
Budd, Chris
Butchers, Matt
Cates, Michael E.
Champneys, Alan R.
Currie, Christine S.M.
Enright, Jessica
Gog, Julia R.
Goriely, Alain
Déirdre Hollingsworth, T.
Hoyle, Rebecca B.
INI Professional Services
Isham, Valerie
Jordan, Joanna
Kaouri, Maha H.
Kavoussanakis, Kostas
Leeks, Jane
Maini, Philip K.
Marr, Christie
Merritt, Clare
Mollison, Denis
Ray, Surajit
Thompson, Robin N.
Wakefield, Alexandra
Wasley, Dawn
Getting the most out of maths: How to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the COVID-19 response in the UK
title Getting the most out of maths: How to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the COVID-19 response in the UK
title_full Getting the most out of maths: How to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the COVID-19 response in the UK
title_fullStr Getting the most out of maths: How to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the COVID-19 response in the UK
title_full_unstemmed Getting the most out of maths: How to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the COVID-19 response in the UK
title_short Getting the most out of maths: How to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the COVID-19 response in the UK
title_sort getting the most out of maths: how to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the covid-19 response in the uk
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9618296/
https://www.ncbi.nlm.nih.gov/pubmed/36323393
http://dx.doi.org/10.1016/j.jtbi.2022.111332
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