Making pandemics big: On the situational performance of Covid-19 mathematical models.
Making pandemics big: On the situational performance of Covid-19 mathematical models.
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DOI：
10.1016/j.socscimed.2022.114907
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发表时间：
2022-05
期刊：
影响因子：
--
通讯作者：
Lancaster K
中科院分区：
文献类型：
--
作者：
Rhodes T;Lancaster K
在本文中，我们追踪了数学模型是如何“足够的证据”和“对政策有用”的。根据参与英国应对新冠肺炎的数学建模人员和其他科学家的采访记录，我们将重点放在2020年3月宣布前所未有的全国封锁之前的两周。我们分析的一个关键线索是流行病是如何“大”的。我们跟随一个特殊装置的工作，即模拟的“倍增时间”。通过跟踪模拟的倍增时间如何在其证据制作的集合中纠缠，我们提请注意多个参与者，包括超越模型和指标，这些参与者影响证据如何与流行病的规模及其政策反应相关。我们提请注意：政策;政府科学咨询基础设施;时间;不确定性;和信仰的飞跃。大流行病的“巨大”及其证据，是在社会和情感实践中，其中的不确定性和疾病是不可分割的微积分。这使得政策建模成为一种“令人不安的科学”。我们认为，情境拟合在目前至少是一样重要的经验拟合时，参加什么模型在政策中执行。
In this paper, we trace how mathematical models are made ‘evidence enough’ and ‘useful for policy’. Working with the interview accounts of mathematical modellers and other scientists engaged in the UK Covid-19 response, we focus on two weeks in March 2020 prior to the announcement of an unprecedented national lockdown. A key thread in our analysis is how pandemics are made 'big'. We follow the work of one particular device, that of modelled ‘doubling-time’. By following how modelled doubling-time entangles in its assemblage of evidence-making, we draw attention to multiple actors, including beyond models and metrics, which affect how evidence is performed in relation to the scale of epidemic and its policy response. We draw attention to: policy; Government scientific advice infrastructure; time; uncertainty; and leaps of faith. The ‘bigness’ of the pandemic, and its evidencing, is situated in social and affective practices, in which uncertainty and dis-ease are inseparable from calculus. This materialises modelling in policy as an ‘uncomfortable science’. We argue that situational fit in-the-moment is at least as important as empirical fit when attending to what models perform in policy.
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DOI：
10.1098/rstb.2021.0001
发表时间：
2021-07-19
期刊：
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
影响因子：
--
作者：
Brooks-Pollock E;Danon L;Jombart T;Pellis L
通讯作者：
Pellis L
影响因子：
3.5
作者：
Eubank, S.;Eckstrand, I;Barrett, C. L.
通讯作者：
Barrett, C. L.
影响因子：
3.8
作者：
Anderson, Ben;Adey, Peter
通讯作者：
Adey, Peter
影响因子：
3.7
作者：
Christley, Robert M.;Mort, Maggie;Latham, Sophia M.
通讯作者：
Latham, Sophia M.
影响因子：
3.2
作者：
Diprose, Rosalyn;Stephenson, Niamh;Hawkins, Gay
通讯作者：
Hawkins, Gay