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.
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.
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DOI：
10.1016/j.jtbi.2022.111332
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发表时间：
2023-01-21
影响因子：
2
通讯作者：
Wasley, Dawn
中科院分区：
文献类型：
--
作者：
Dangerfield, Ciara E;David Abrahams, I;Budd, Chris;Butchers, Matt;Cates, Michael E;Champneys, Alan R;Currie, Christine S M;Enright, Jessica;Gog, Julia R;Goriely, Alain;Deirdre Hollingsworth, T;Hoyle, Rebecca B;Ini Professional Services;Isham, Valerie;Jordan, Joanna;Kaouri, Maha H;Kavoussanakis, Kostas;Leeks, Jane;Maini, Philip K;Marr, Christie;Merritt, Clare;Mollison, Denis;Ray, Surajit;Thompson, Robin N;Wakefield, Alexandra;Wasley, Dawn
2020年3月，数学成为向英国政府提供的应对新冠肺炎疫情的科学建议的关键部分。数学和统计模型提供了有关病毒传播和不同干预措施的潜在影响的关键信息。这一挑战的空前规模导致英国的流行病学模型界被推到了极限。与此同时，全国各地的数学模型师都热衷于用他们的知识和技能来支持新冠肺炎的建模工作。然而，需要协调对流行病学建模的这种突如其来的巨大兴趣，以提供亟需的支持，并限制流行病学建模人员的负担，这些负担已经非常紧张。在这篇文章中，我们描述了2020年春季在英国设立的三项倡议，以协调数学科学研究社区支持新冠肺炎的数学建模。每项倡议都有不同的主要目标，并致力于最大限度地发挥不同项目之间的协同作用。我们反思吸取的经验教训，强调先前存在的研究协作和协调中心在推动这些举措取得成功方面的关键作用。最后，我们就科学研究界可以更好地为未来的大流行做好准备的重要方式提出建议。这份稿件是作为《新冠肺炎模式与应对未来大流行病》主题期刊的一部分提交的。
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”.