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Titlebook: COVID-19 Epidemiology and Virus Dynamics; Nonlinear Physics an Till D. Frank Book 2022 The Editor(s) (if applicable) and The Author(s), und

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發(fā)表于 2025-3-21 16:07:42 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱COVID-19 Epidemiology and Virus Dynamics
副標(biāo)題Nonlinear Physics an
編輯Till D. Frank
視頻videohttp://file.papertrans.cn/221/220493/220493.mp4
概述Analyzes quantitatively COVID-19 outbreaks in various countries around the globe.Makes use of mathematical models of epidemiology such as the SIR and SEIR models.Discusses the impacts of measures impl
叢書(shū)名稱Understanding Complex Systems
圖書(shū)封面Titlebook: COVID-19 Epidemiology and Virus Dynamics; Nonlinear Physics an Till D. Frank Book 2022 The Editor(s) (if applicable) and The Author(s), und
描述.This book addresses the COVID-19 pandemic from a quantitative perspective based on mathematical models and methods largely used in nonlinear physics. It aims to study COVID-19 epidemics in countries and SARS-CoV-2 infections in individuals from the nonlinear physics perspective and to model explicitly COVID-19 data observed in countries and virus load data observed in COVID-19 patients...The first part of this book provides a short technical introduction into amplitude spaces given by eigenvalues, eigenvectors, and amplitudes.In the second part of the book, mathematical models of epidemiology are introduced such as the SIR and SEIR models and applied to describe COVID-19 epidemics in various countries around the world. In the third part of the book, virus dynamics models are considered and applied to infections in COVID-19 patients...This book is written for researchers, modellers, and graduate students in physics and medicine, epidemiology?and?virology,?biology, applied?mathematics,?and computer sciences. This?book identifies the relevant mechanisms behind past?COVID-19 outbreaks and in doing so can help efforts?to?stop future COVID-19 outbreaks and other epidemic outbreaks. Like
出版日期Book 2022
關(guān)鍵詞Prevention of COVID-19 virus transmission; Self-organization in contagious diseases; Beyond COVID-19; B
版次1
doihttps://doi.org/10.1007/978-3-030-97178-6
isbn_softcover978-3-030-97180-9
isbn_ebook978-3-030-97178-6Series ISSN 1860-0832 Series E-ISSN 1860-0840
issn_series 1860-0832
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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發(fā)表于 2025-3-21 22:30:42 | 只看該作者
板凳
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地板
發(fā)表于 2025-3-22 07:01:06 | 只看該作者
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發(fā)表于 2025-3-22 09:59:14 | 只看該作者
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發(fā)表于 2025-3-22 13:34:23 | 只看該作者
K?iti Hasida,Shun Ishizaki,Hitoshi Isaharatic dynamical systems. The chapter focuses on the SIR model and SIR-type models. The amplitude space description is worked out in detail and the SI order parameter is determined. It is demonstrated that within the SIR modeling framework, the SI order parameter determines the initial stage of epidemi
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發(fā)表于 2025-3-22 18:04:59 | 只看該作者
Domenico Parisi,Donatella Ferranteiables that are minimally necessary to obtain an autonomous description in amplitude space and all remaining variables. The nonlinear physics approach is then presented for this minimal closed space. Amplitude equations for the SEIR model and SEIR-type models are explicitly derived and their SEI ord
8#
發(fā)表于 2025-3-22 21:44:18 | 只看該作者
https://doi.org/10.1007/978-94-009-3645-4, in particular. It begins with the introduction of the minimal subspace of variables leading to an autonomous amplitude space description in the linear domain. Such autonomous amplitude space descriptions are worked out in detail for the SIR and SEIR models. The benefit of this approach is demonstr
9#
發(fā)表于 2025-3-23 05:08:40 | 只看該作者
Domenico Parisi,Donatella Ferrantebers of the SIR and SEIR models are presented. Subsequently, the next generation method is presented that allows to determine reproduction numbers for a variety of high-dimensional compartmental model. It is discussed that reproduction numbers can be regarded as bifurcation parameters that determine
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發(fā)表于 2025-3-23 06:07:24 | 只看該作者
Natural Language Generation Systemsention measures can affect structural properties of populations and, in doing so, induce bifurcations from unstable disease-free states towards stable disease-free states. As a result of such bifurcations, epidemics begin to subside. The sign switching phenomenon of maximal eigenvalues is explored t
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