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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

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Dangerfield, Ciara E., Abrahams, I. David, Budd, Chris, Butchers, Matt, Cates, Michael E., Champneys, Alan R., Currie, Christine S. M., Enright, Jessica, Gog, Julia R., Goriely, Alain et al.
(2022) 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. Journal of Theoretical Biology, 557 . 111332. doi:10.1016/j.jtbi.2022.111332 ISSN 0022-5193.

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Official URL: https://doi.org/10.1016/j.jtbi.2022.111332

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Abstract

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.

Item Type: Journal Article
Subjects: R Medicine > RA Public aspects of medicine
Divisions: Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- )
Faculty of Science, Engineering and Medicine > Science > Mathematics
Library of Congress Subject Headings (LCSH): COVID-19 (Disease) -- Mathematical models, Epidemics -- Mathematical models, COVID-19 Pandemic, 2020- -- Mathematical models, COVID-19 (Disease) -- Forecasting -- Evaluation, COVID-19 (Disease) -- Great Britain -- Prevention -- Mathematical models
Journal or Publication Title: Journal of Theoretical Biology
Publisher: Elsevier
ISSN: 0022-5193
Official Date: 21 January 2022
Dates:
DateEvent
21 January 2022Published
14 November 2022Available
18 October 2022Accepted
Volume: 557
Number of Pages: 12
Article Number: 111332
DOI: 10.1016/j.jtbi.2022.111332
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Description:

Free access

Date of first compliant deposit: 26 October 2022
Date of first compliant Open Access: 29 November 2022
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
EP/R014604/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
EP/V053507/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
ST/V00221X/1UK Research and Innovationhttp://dx.doi.org/10.13039/100014013
MR/V038613/1UK Research and Innovationhttp://dx.doi.org/10.13039/100014013
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