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Cited by 76COVID-19 epidemiological studiesAcademic Publishing and Open AccessSARS-CoV-2 and COVID-19 Research

Modelling that shaped the early COVID-19 pandemic response in the UK

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Brooks-Pollock, Ellen, Danon, Leon, Jombart, Thibaut, Pellis, Lorenzo·2021·Philosophical Transactions of the Royal Society B
DOI 10.1098/rstb.2021.0001PMC PMC8165593
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Abstract

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’.

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  • Mathematical models of disease transmission and control are a key tool for responding to infectious disease outbreaks and guiding policy, for example by projecting epidemic trajectories, healthcare demand, and intervention impact.

    “Mathematical models of disease transmission and control are a key tool that can be deployed in response to infectious disease outbreaks and are used to guide policy, for example by projecting plausible epidemic trajectories and expected healthcare demand and assessing the potential impact of interventions (19,20).”

    From Marburg virus disease outbreaks, mathematical models, and disease parameters: a systematic review (2024) · cites this paper as [19]

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Authors
Brooks-Pollock, E., Danon, L., Jombart, T., & Pellis, L.
Affiliations
  • 1 Bristol Veterinary School, University of Bristol, Bristol BS40 5DU, UK
  • 3 Department of Engineering Mathematics, University of Bristol, Bristol BS8 1TW, UK
  • London School of Hygiene & Tropical Medicine (GB)
  • University of Manchester (GB)
ORCID
Venue
Philosophical Transactions of the Royal Society B
Publisher
The Royal Society
Published
2021-05-31
Volume
376
Issue
1829
Pages
20210001-20210001
ISSN
  • 0962-8436 (ISSN-L)
  • 1471-2970
DOI
10.1098/rstb.2021.0001
PMC
PMC8165593
OpenAlex
W3164986408
Cited by
76
References
0
Citations by year
2026: 5 · 2025: 15 · 2024: 17 · 2023: 16 · 2022: 16 · 2021: 7
FWCI
5.41
Type
journal article
Language
en
Open access
Licence
Locations
  • Philosophical Transactions of the Royal Society B Biological Sciences (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research Explorer (The University of Manchester) (publishedVersion, other-oa)
  • Bristol Research (University of Bristol) (publishedVersion, cc-by)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
  • Explore Bristol Research (submittedVersion, cc-by)
Funders
  • Medical Research Council (MC/PC/19067, MR/V038613/1)
  • Engineering and Physical Sciences Research Council (EP/N510129/1, EP/V051555/1)
Topics
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Social Sciences › Decision Sciences › Information Systems and Management › Academic Publishing and Open Access
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
Keywords
COVID-19 pandemic response, epidemic modeling, sage, science-policy interface, transparency and reproducibility, academic publishing practices, academic credit
MeSH terms
COVID-19, SARS-CoV-2, United Kingdom, Humans, Pandemics

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