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2019冠状病毒病大流行模型:比较分析

Models for COVID-19 Pandemic: A Comparative Analysis.

作者信息

Adiga Aniruddha, Dubhashi Devdatt, Lewis Bryan, Marathe Madhav, Venkatramanan Srinivasan, Vullikanti Anil

机构信息

BIOCOMPLEXITY INSTITUTE AND INITITIATIVE, UNIVERSITY OF VIRGINIA.

DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING, CHALMERS UNIVERSITY.

出版信息

ArXiv. 2020 Sep 21:arXiv:2009.10014v1.

PMID:32995366
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7523122/
Abstract

COVID-19 pandemic represents an unprecedented global health crisis in the last 100 years. Its economic, social and health impact continues to grow and is likely to end up as one of the worst global disasters since the 1918 pandemic and the World Wars. Mathematical models have played an important role in the ongoing crisis; they have been used to inform public policies and have been instrumental in many of the social distancing measures that were instituted worldwide. In this article we review some of the important mathematical models used to support the ongoing planning and response efforts. These models differ in their use, their mathematical form and their scope.

摘要

新冠疫情是过去100年来前所未有的全球健康危机。其对经济、社会和健康的影响持续扩大,很可能成为自1918年大流行和两次世界大战以来最严重的全球灾难之一。数学模型在这场持续的危机中发挥了重要作用;它们被用于为公共政策提供信息,并在全球范围内实施的许多社会 distancing 措施中发挥了重要作用。在本文中,我们回顾了一些用于支持当前规划和应对工作的重要数学模型。这些模型在用途、数学形式和范围上有所不同。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f476/7523122/5d2e31b0bb05/nihpp-2009.10014v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f476/7523122/5d2e31b0bb05/nihpp-2009.10014v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f476/7523122/5d2e31b0bb05/nihpp-2009.10014v1-f0001.jpg

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本文引用的文献

1
Robust T Cell Immunity in Convalescent Individuals with Asymptomatic or Mild COVID-19.无症状或轻症 COVID-19 康复者体内具有强大的 T 细胞免疫。
Cell. 2020 Oct 1;183(1):158-168.e14. doi: 10.1016/j.cell.2020.08.017. Epub 2020 Aug 14.
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COVID-19 healthcare demand and mortality in Sweden in response to non-pharmaceutical mitigation and suppression scenarios.瑞典针对非药物缓解和抑制情景的 COVID-19 医疗需求和死亡率。
Int J Epidemiol. 2020 Oct 1;49(5):1443-1453. doi: 10.1093/ije/dyaa121.
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Mathematical models to guide pandemic response.
指导疫情应对的数学模型。
Science. 2020 Jul 24;369(6502):368-369. doi: 10.1126/science.abd1668.
4
Managing Coronavirus Disease 2019 Spread With Voluntary Public Health Measures: Sweden as a Case Study for Pandemic Control.用自愿性公共卫生措施控制 2019 年冠状病毒病传播:以瑞典作为大流行控制的案例研究。
Clin Infect Dis. 2020 Dec 15;71(12):3174-3181. doi: 10.1093/cid/ciaa864.
5
Critiqued coronavirus simulation gets thumbs up from code-checking efforts.受批评的新冠病毒模拟通过代码检查获得认可。
Nature. 2020 Jun;582(7812):323-324. doi: 10.1038/d41586-020-01685-y.
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Infodemic and Risk Communication in the Era of CoV-19.新冠疫情时代的信息疫情与风险沟通
Adv Biomed Res. 2020 Mar 11;9:10. doi: 10.4103/abr.abr_47_20. eCollection 2020.
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Special report: The simulations driving the world's response to COVID-19.特别报道:推动全球应对新冠疫情的模拟分析
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Science. 2020 May 1;368(6490):493-497. doi: 10.1126/science.abb4218. Epub 2020 Mar 25.
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The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak.旅行限制对 2019 年新型冠状病毒(COVID-19)疫情传播的影响。
Science. 2020 Apr 24;368(6489):395-400. doi: 10.1126/science.aba9757. Epub 2020 Mar 6.
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Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the U.S.美国季节性流感实时多模式集合预测的准确性
PLoS Comput Biol. 2019 Nov 22;15(11):e1007486. doi: 10.1371/journal.pcbi.1007486. eCollection 2019 Nov.