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Mathematical models of the spread and consequences of the SARS-CoV-2 pandemics
Journal of Mathematics in Industry Pub Date : 2021-09-20 , DOI: 10.1186/s13362-021-00111-w
Alessandra Micheletti 1 , Adérito Araújo 2 , Neil Budko 3 , Ana Carpio 4 , Matthias Ehrhardt 5
Affiliation  

The SARS coronavirus 2 (SARS-CoV-2) pandemic of coronavirus disease-19 (COVID-19) has changed the lives of everyone on the planet. As a new disease with a significant mortality rate and no known pharmaceutical intervention or curative treatment to date, COVID-19 has stimulated a huge worldwide academic research effort on every aspect of the spread of the virus and the effectiveness of containment measures, without neglecting the drawbacks that such measures have brought to the economy, society, and public health.

Within this framework, mathematicians and statisticians have contributed (and are actually still working on) models capable of capturing and focusing on the main components of epidemic spread and symptom severity, such as the dependence on patient age, the presence and role of asymptomatic infected individuals, the expected utilization of hospitals and intensive care units, the identification of the main sites and sources of infection (schools, restaurants, workplaces, etc.), the impact of lockdown measures.

In the highly heterogeneous scenario of COVID-19 epidemic spread, mathematical models adapted to national or more local situations are useful to provide policy makers with better insight into the consequences of different possible containment strategies, including the organization and optimization of vaccination campaigns.

For this reason, the European Consortium for Mathematics in Industry (ECMI) saw an urgency to provide policy makers with scientifically reliable studies on the many aspects of the problem, and this was our goal in producing this special issue of the Journal of Mathematics in Industry. This special issue is devoted to articles that propose data-driven mathematical and statistical models of the spread of the SARS-CoV-2 virus and/or its foreseeable consequences for public health, society, industry, business, and technology.

Actually, editorial activities such as these are only a first step toward the creation of a “scientific policy” that can truly counter the emergence of new health, environmental, and social emergencies. Such a scientific policy should act in a more systemic way, not just in the presence of emergencies. It should be the result of more rigorous collaboration between scientists from different disciplines (mathematicians, epidemiologists, virologists, environmental scientists, economists, social scientists, etc.) on the one hand, and between academia and science on the other: in contrast to the academic tendency to specialize and separate different fields of knowledge, policy makers should promote the “breaking of interdisciplinary silos” and realize an alliance between policy and science to more consciously address long-term policy strategic decisions.

The COVID-19 pandemic is just one example of the risks that humans face and that must be urgently addressed. The major challenge facing humanity in the coming years to prevent the rise of further emergencies is the environmental problem. As reported in the UNEP Frontiers 2016 Report [2], “climate change is a major factor for disease emergence. It influences the environmental conditions that can enable or disable the survival, reproduction, abundance, and distribution of pathogens, vectors, and hosts, as well as the means of disease transmission and the outbreak frequency. Growing evidence suggest that outbreaks of epidemic diseases may become more frequent as climate continues to change.”

Such problems can only be addressed with serious alignment of goals between scientists and policymakers, with the help and planning of good communication strategies, cf. [1].

  1. 1.

    Kano H, Hayashi TI. A framework for implementing evidence in policymaking: perspectives and phases of evidence evaluation in the science-policy interaction. Environ Sci Policy. 2021;116:86–95.

    Article Google Scholar

  2. 2.

    UNEP frontiers 2016 report: emerging issues of environmental concern. Nairobi: United Nations Environment Programme. ISBN:978-92-807-3553-6.

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Affiliations

  1. Università degli Studi di Milano, Milano, Italy

    Alessandra Micheletti

  2. University of Coimbra, Coimbra, Portugal

    Adérito Araújo

  3. Delft University of Technology, Delft, The Netherlands

    Neil Budko

  4. Universidad Complutense de Madrid, Madrid, Spain

    Ana Carpio

  5. Bergische Universität Wuppertal, Wuppertal, Germany

    Matthias Ehrhardt

Authors
  1. Alessandra MichelettiView author publications

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  2. Adérito AraújoView author publications

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  3. Neil BudkoView author publications

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  4. Ana CarpioView author publications

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  5. Matthias EhrhardtView author publications

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Corresponding author

Correspondence to Alessandra Micheletti.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Micheletti, A., Araújo, A., Budko, N. et al. Mathematical models of the spread and consequences of the SARS-CoV-2 pandemics. J.Math.Industry 11, 15 (2021). https://doi.org/10.1186/s13362-021-00111-w

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中文翻译：
SARS-CoV-2 大流行的传播和后果的数学模型

SARS 冠状病毒 2 (SARS-CoV-2) 冠状病毒病 19 (COVID-19) 大流行改变了地球上每个人的生活。作为一种死亡率很高且迄今为止尚无已知药物干预或治疗方法的新疾病，COVID-19 在不忽视病毒传播的各个方面和遏制措施的有效性的情况下，激发了全球范围内的巨大学术研究努力。这些措施给经济、社会和公共卫生带来的弊端。

在这个框架内，数学家和统计学家已经贡献（并且实际上仍在研究）能够捕捉和关注流行病传播和症状严重程度的主要组成部分的模型，例如对患者年龄的依赖、无症状感染者的存在和作用、医院和重症监护室的预期利用率、主要感染地点和来源（学校、餐馆、工作场所等）的确定，封锁措施的影响。

在 COVID-19 流行病传播的高度异质性情况下，适用于国家或更多地方情况的数学模型有助于政策制定者更好地了解不同可能的遏制策略的后果，包括疫苗接种活动的组织和优化。

出于这个原因，欧洲工业数学联盟 (ECMI) 认为迫切需要为决策者提供有关该问题许多方面的科学可靠的研究，这就是我们制作《工业数学杂志》特刊的目标. 本期特刊专门刊登提出 SARS-CoV-2 病毒传播和/或其对公共卫生、社会、工业、商业和技术的可预见后果的数据驱动数学和统计模型的文章。

实际上，诸如此类的编辑活动只是朝着制定能够真正应对新的健康、环境和社会紧急情况的“科学政策”迈出的第一步。这样的科学政策应该以更系统的方式采取行动，而不仅仅是在出现紧急情况时。一方面，它应该是来自不同学科的科学家（数学家、流行病学家、病毒学家、环境科学家、经济学家、社会科学家等）之间更严格合作的结果，另一方面是学术界和科学界之间更严格合作的结果：与专业化和分离不同知识领域的学术倾向，

COVID-19 大流行只是人类面临且必须紧急解决的风险的一个例子。未来几年，人类在防止进一步紧急情况发生方面面临的主要挑战是环境问题。正如环境署前沿 2016 年报告 [2] 中所报道的那样，“气候变化是疾病出现的一个主要因素。它影响着能够使病原体、媒介物和宿主的生存、繁殖、丰度和分布成为可能或无效的环境条件，以及疾病传播的方式和爆发频率。越来越多的证据表明，随着气候的持续变化，流行病的爆发可能会变得更加频繁。”

这些问题只能通过科学家和政策制定者之间的目标的认真协调，以及良好沟通策略的帮助和规划来解决，参见。[1]。

  1. 1.

    卡诺 H，林 TI。在决策中实施证据的框架：科学政策互动中证据评估的观点和阶段。环境科学政策。2021；116：86-95。

    文章 谷歌学术

  2. 2.

    环境署前沿 2016 年报告：新出现的环境问题。内罗毕：联合国环境规划署。ISBN：978-92-807-3553-6。

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隶属关系

  1. Università degli Studi di Milano，米兰，意大利

    亚历山德拉·米凯莱蒂

  2. 科英布拉大学，科英布拉，葡萄牙

    阿德里托·阿劳霍

  3. 代尔夫特理工大学，荷兰代尔夫特

    尼尔·布德科

  4. 马德里康普顿斯大学，马德里，西班牙

    安娜卡皮奥

  5. Bergische Universität Wuppertal，伍珀塔尔，德国

    马蒂亚斯·埃尔哈特

作者
  1. Alessandra Micheletti查看作者出版物

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  2. Adérito Araújo查看作者出版物

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  3. Neil Budko查看作者出版物

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  4. Ana Carpio查看作者出版物

    您也可以在PubMed Google Scholar中搜索此作者 

  5. Matthias Ehrhardt查看作者出版物

    您也可以在PubMed Google Scholar中搜索此作者 

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与亚历山德拉·米凯莱蒂的通信。

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Micheletti, A.、Araújo, A.、Budko, N.等。SARS-CoV-2 大流行的传播和后果的数学模型。J.Math.Industry 11, 15 (2021)。https://doi.org/10.1186/s13362-021-00111-w

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更新日期：2021-09-21
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