Modelling the COVID-19 pandemic in context: an international participatory approach.
Modelling the COVID-19 pandemic in context: an international participatory approach.
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DOI：
10.1136/bmjgh-2020-003126
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发表时间：
2020-12
影响因子：
8.1
通讯作者：
CoMo Consortium
中科院分区：
文献类型：
--
作者：
Aguas R;White L;Hupert N;Shretta R;Pan-Ngum W;Celhay O;Moldokmatova A;Arifi F;Mirzazadeh A;Sharifi H;Adib K;Sahak MN;Franco C;Coutinho R;CoMo Consortium
SARS-CoV-2大流行对社会多个层面产生了前所未有的影响。这场大流行不仅使一些卫生系统完全不堪重负，而且还改变了科学证据的分享方式，加快了科学家、政策制定者和更广泛的公众发表和消费此类证据的速度。更重要的是，这场大流行给决策者带来了巨大的挑战，他们不得不在几乎没有经验科学证据的情况下实施高度破坏性的遏制措施来支持他们的决策过程。鉴于这种数据的缺乏，预测性数学模型发挥着越来越重要的作用。在高收入国家，老牌研究小组为政策制定者提供建议的历史由来已久，而普遍缺乏转换能力意味着低收入和中等收入国家的政策制定者往往无法获得数学模型。在这里，我们描述了一种旨在绕过这一差距的参与式建模方法。我们的方法包括建立一个由传染病模型师和其他公共卫生专家组成的国际小组，最终成立了新冠肺炎模型(COMO)联盟。在这里，我们将介绍该联盟的组成、运作方式、所使用的数学模型，以及至关重要的是，该联盟成员与其各自的地方政策制定者和卫生部之间促进的高度接触。
The SARS-CoV-2 pandemic has had an unprecedented impact on multiple levels of society. Not only has the pandemic completely overwhelmed some health systems but it has also changed how scientific evidence is shared and increased the pace at which such evidence is published and consumed, by scientists, policymakers and the wider public. More significantly, the pandemic has created tremendous challenges for decision-makers, who have had to implement highly disruptive containment measures with very little empirical scientific evidence to support their decision-making process. Given this lack of data, predictive mathematical models have played an increasingly prominent role. In high-income countries, there is a long-standing history of established research groups advising policymakers, whereas a general lack of translational capacity has meant that mathematical models frequently remain inaccessible to policymakers in low-income and middle-income countries. Here, we describe a participatory approach to modelling that aims to circumvent this gap. Our approach involved the creation of an international group of infectious disease modellers and other public health experts, which culminated in the establishment of the COVID-19 Modelling (CoMo) Consortium. Here, we describe how the consortium was formed, the way it functions, the mathematical model used and, crucially, the high degree of engagement fostered between CoMo Consortium members and their respective local policymakers and ministries of health.
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影响因子：
82.9
作者：
He, Xi;Lau, Eric H. Y.;Leung, Gabriel M.
通讯作者：
Leung, Gabriel M.
影响因子：
9.3
作者：
Jarvis, Christopher I.;Van Zandvoort, Kevin;Edmunds, W. John
通讯作者：
Edmunds, W. John
DOI：
10.15585/mmwr.mm6912e2
发表时间：
2020-03-27
期刊：
MMWR. Morbidity and mortality weekly report
影响因子：
--
作者：
CDC COVID-19 Response Team
通讯作者：
CDC COVID-19 Response Team
影响因子：
5.4
作者：
Leach, Melissa;Scoones, Ian
通讯作者：
Scoones, Ian
影响因子：
2.9
作者：
Mansnerus, Erika
通讯作者：
Mansnerus, Erika