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. 2021 Jul 19;376(1829):20210001.
doi: 10.1098/rstb.2021.0001. Epub 2021 May 31.

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

Ellen Brooks-Pollock  1   2 , Leon Danon  3 , Thibaut Jombart  4   5 , Lorenzo Pellis  6   7
Affiliations

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

Ellen Brooks-Pollock et al. Philos Trans R Soc Lond B Biol Sci. .

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'.

Keywords: COVID-19; infectious disease modelling; modelling for policy.

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Figures

Figure 1.
Figure 1.
Collaboration network for SPI-M-O contributors. Graph created from PubMed results on 23 March 2021 with the list of SPI-M contributors stated on the UK Government website [7]. Nodes represent SPI-M contributors and edges represent one or more co-authored publications between contributors listed in PubMed. Colours represent communities of densely connected researchers identified using the spinglass algorithm [9,10]. London School of Hygiene and Tropical Medicine: yellow; Imperial: green; Warwick/Manchester/Lancaster/Bristol/Exeter: orange; Oxford: light blue; PHE/Cambridge: dark blue. Contributors listed online with no connections are not shown (16 individuals).
Figure 2.
Figure 2.
Key components of disease transmission models, and the contributing inputs and parameters. (Online version in colour.)
Figure 3.
Figure 3.
An illustration of the impact of exponential growth when social distancing rules are relaxed and reimposed. (Online version in colour.)
Figure 4.
Figure 4.
COVID-19 epidemic curve with Special Issue papers marked on, indicating when the work was developed.
See this image and copyright information in PMC

References

    1. World Health Organization. WHO Timeline - COVID-19. 2021. See https://www.who.int/news/item/27-04-2020-who-timeline---covid-19 (accessed on 9 April 2021).
    1. Public Health England. 2020 Official UK Coronavirus Dashboard. See https://coronavirus.data.gov.uk/ (accessed on 9 April 2021).
    1. Prime Minister's Office. 2020. Prime Minister's statement on coronavirus (COVID-19): 16 March 2020. GOV.UK. See https://www.gov.uk/government/speeches/pm-statement-on-coronavirus-16-ma... (accessed on 9 April 2021).
    1. Government Office for Science. 2020 About the Scientific Advisory Group for Emergencies (SAGE). See https://www.gov.uk/government/organisations/scientific-advisory-group-fo... (accessed on 8 April 2021).
    1. Government Office for Science. 2020 Scientific evidence supporting the government response to coronavirus (COVID-19). See https://www.gov.uk/government/collections/scientific-evidence-supporting... (accessed on 8 April 2021).

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