Abstract
The coronavirus disease 2019 (COVID-19) pandemic has disrupted the lives of billions across the world. Mathematical modelling has been a key tool deployed throughout the pandemic to explore the potential public health impact of an unmitigated epidemic. The results of such studies have informed governments' decisions to implement non-pharmaceutical interventions to control the spread of the virus. In this article, we explore the complex relationships between models, decision-making, the media and the public during the COVID-19 pandemic in the United Kingdom of Great Britain and Northern Ireland (UK). Doing so not only provides an important historical context of COVID-19 modelling and how it has shaped the UK response, but as the pandemic continues and looking towards future pandemic preparedness, understanding these relationships and how they might be improved is critical. As such, we have synthesized information gathered via three methods: a survey to publicly list attendees of the Scientific Advisory Group for Emergencies, the Scientific Pandemic Influenza Group on Modelling and other comparable advisory bodies, interviews with science communication experts and former scientific advisors, and reviewing some of the key COVID-19 modelling literature from 2020. Our research highlights the desire for increased bidirectional communication between modellers, decision-makers and the public, as well as the need to convey uncertainty inherent in transmission models in a clear manner. These aspects should be considered carefully ahead of the next emergency response.
Highlights
Since the discovery of the novel coronavirus SARS-CoV-2 in late 2019, the lives of billions of people across the planet have been substantially disrupted
This allowed the exploration of urgent public health questions, for example: how many people have been infected with the virus? Might the unmitigated spread of the virus overwhelm healthcare systems? [5,6] The results of such studies are one piece of evidence used to inform governments’ decisions to take unprecedented actions to control the spread of the virus in the form of stringent non-pharmaceutical interventions (NPIs)
This article has sought to provide a broader perspective on the scope and use of mathematical modelling throughout the COVID-19 pandemic, in informing policy in the United Kingdom (UK)
Summary
Since the discovery of the novel coronavirus SARS-CoV-2 in late 2019, the lives of billions of people across the planet have been substantially disrupted This highly transmissible virus, which causes coronavirus disease 2019 (COVID-19), has threatened the stability of healthcare systems globally with the official death count sitting at over 3.8 million people as of 15 June 2021 [1]. As the initial epidemic unfolded in Wuhan in early 2020, scientists sought to understand rapidly the key epidemiological characteristics of the virus, such as the serial interval distribution and infection fatality ratio, in order to parametrize such models [2,3,4]. As well as reducing transmission of the virus, these measures have drastically disrupted the normal functioning of society with no section of the population left unaffected by the pandemic and its control
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