Evidence map›Paper›PMID 36323393›Full record

ArticleJournal of theoretical biology2023

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.

Ciara E Dangerfield, I David Abrahams, Chris Budd, Matt Butchers, Michael E Cates, Alan R Champneys, Christine S M Currie, Jessica Enright, Julia R Gog, Alain Goriely and 16 more

Abstract read
In one paragraph

Article in Journal of theoretical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Modelling practices, data provisioning, sharing and dissemination needs for pandemic decision-making: a European survey-based modellers' perspective, 2020 to 2022.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

26 authors.

Ciara E DangerfieldIsaac Newton Institute to Mathematical Sciences, University of Cambridge, United Kingdom; Joint UNIversities Pandemic and Epidemiological Research (JUNIPER) Consortium, United Kingdom(1). Electronic address: ced57@cam.ac.uk.
I David AbrahamsDepartment for Applied Mathematics and Theoretical Physics, University of Cambridge, United Kingdom.
Chris BuddDepartment of Mathematics, University of Bath, United Kingdom.
Matt ButchersDepartment of Mathematics, University of Bath, United Kingdom.
Michael E CatesDepartment for Applied Mathematics and Theoretical Physics, University of Cambridge, United Kingdom.
Alan R ChampneysDepartment of Engineering Mathematics, University of Bristol, United Kingdom.
Christine S M CurrieSchool of Mathematical Sciences, University of Southampton, United Kingdom.
Jessica EnrightSchool of Computing Science, University of Glasgow, United Kingdom.
Julia R GogJoint UNIversities Pandemic and Epidemiological Research (JUNIPER) Consortium, United Kingdom(1); Department for Applied Mathematics and Theoretical Physics, University of Cambridge, United Kingdom.
Alain GorielyMathematical Institute, University of Oxford, United Kingdom.
T Déirdre HollingsworthJoint UNIversities Pandemic and Epidemiological Research (JUNIPER) Consortium, United Kingdom(1); Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, United Kingdom.
Rebecca B HoyleSchool of Mathematical Sciences, University of Southampton, United Kingdom.
Ini Professional ServicesIsaac Newton Institute to Mathematical Sciences, University of Cambridge, United Kingdom.
Valerie IshamDepartment of Statistical Science, University College London, United Kingdom.
Joanna JordanIndependent, United Kingdom.
Maha H KaouriIsaac Newton Institute to Mathematical Sciences, University of Cambridge, United Kingdom.
Kostas KavoussanakisEPCC, The University of Edinburgh, United Kingdom.
Jane LeeksIsaac Newton Institute to Mathematical Sciences, University of Cambridge, United Kingdom.
Philip K MainiMathematical Institute, University of Oxford, United Kingdom.
Christie MarrIsaac Newton Institute to Mathematical Sciences, University of Cambridge, United Kingdom.
Clare MerrittIsaac Newton Institute to Mathematical Sciences, University of Cambridge, United Kingdom.
Denis MollisonDepartment of Actuarial Mathematics and Statistics, Heriot-Watt University, United Kingdom.
Surajit RaySchool of Mathematics and Statistics, University of Glasgow, United Kingdom.
Robin N ThompsonMathematics Institute, University of Warwick, United Kingdom; Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, United Kingdom.
Alexandra WakefieldThe Royal Society, London, United Kingdom.
Dawn WasleyInternational Centre for Mathematical Sciences, University of Edinburgh & Heriot-Watt University, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Indexed as

COVID-19PandemicsHumansLearningMathematicsUnited KingdomCOVID-19Knowledge exchangeMathematical modellingResearch co-ordination

Identifiers

PMID36323393
PMCPMC9618296

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.