Modelling that shaped the early COVID-19 pandemic response in the UK-Reference-Cited by-同舟云学术

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

Published:2021-05-31 Issue:1829 Volume:376 Page:
ISSN:0962-8436
Container-title:Philosophical Transactions of the Royal Society B: Biological Sciences
language:en
Short-container-title:Phil. Trans. R. Soc. B

Author:

Brooks-Pollock Ellen¹²^ORCID,Danon Leon³^ORCID,Jombart Thibaut⁴⁵^ORCID,Pellis Lorenzo⁶⁷^ORCID

Affiliation:

1. Bristol Veterinary School, University of Bristol, Bristol BS40 5DU, UK

2. NIHR Health Protection Research Unit (HPRU) in Behavioural Science and Evaluation, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK

3. Department of Engineering Mathematics, University of Bristol, Bristol BS8 1TW, UK

4. Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK

5. MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, UK

6. Department of Mathematics, University of Manchester, Manchester M13 9PL, UK

7. The Alan Turing Institute, London, UK

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’.

Funder

Medical Research Council

Engineering and Physical Sciences Research Council

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology

Link

https://royalsocietypublishing.org/doi/pdf/10.1098/rstb.2021.0001

Reference47 articles.

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).

2. Public Health England. 2020 Official UK Coronavirus Dashboard. See https://coronavirus.data.gov.uk/ (accessed on 9 April 2021).

3. 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-march-2020 (accessed on 9 April 2021).

4. Government Office for Science. 2020 About the Scientific Advisory Group for Emergencies (SAGE). See https://www.gov.uk/government/organisations/scientific-advisory-group-for-emergencies/about (accessed on 8 April 2021).

5. 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-the-government-response-to-coronavirus-covid-19 (accessed on 8 April 2021).

Cited by 60 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. European students and staff in higher education in the UK: Statistics, challenges and opportunities;International Journal of Educational Development;2024-10

2. Fitting Epidemic Models to Data: A Tutorial in Memory of Fred Brauer;Bulletin of Mathematical Biology;2024-07-25

3. Canada’s provincial COVID-19 pandemic modelling efforts: A review of mathematical models and their impacts on the responses;Canadian Journal of Public Health;2024-07-25

4. When should lockdown be implemented? Devising cost-effective strategies for managing epidemics amid vaccine uncertainty;PLOS Computational Biology;2024-07-18

5. Opportunities to strengthen respiratory virus surveillance systems in Australia: lessons learned from the COVID-19 response;Communicable Diseases Intelligence;2024-07-17