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Epidemic as a natural process

Mathematical epidemiology is a well-recognized discipline to model infectious diseases. It also provides guidance for public health officials to limit outbreaks. Nevertheless, epidemics take societies by surprise every now and then, for example, when the Ebola virus epidemic raged seemingly unrestra...

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Detalles Bibliográficos
Autores principales: Koivu-Jolma, Mikko, Annila, Arto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7094378/
https://www.ncbi.nlm.nih.gov/pubmed/29534891
http://dx.doi.org/10.1016/j.mbs.2018.03.012
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author Koivu-Jolma, Mikko
Annila, Arto
author_facet Koivu-Jolma, Mikko
Annila, Arto
author_sort Koivu-Jolma, Mikko
collection PubMed
description Mathematical epidemiology is a well-recognized discipline to model infectious diseases. It also provides guidance for public health officials to limit outbreaks. Nevertheless, epidemics take societies by surprise every now and then, for example, when the Ebola virus epidemic raged seemingly unrestrained in Western Africa. We provide insight to this capricious character of nature by describing the epidemic as a natural process, i.e., a phenomenon governed by thermodynamics. Our account, based on statistical mechanics of open systems, clarifies that it is impossible to predict accurately epidemic courses because everything depends on everything else. Nonetheless, the thermodynamic theory yields a comprehensive and analytical view of the epidemic. The tenet subsumes various processes in a scale-free manner from the molecular to the societal levels. The holistic view accentuates overarching procedures in arresting and eradicating epidemics.
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spelling pubmed-70943782020-03-25 Epidemic as a natural process Koivu-Jolma, Mikko Annila, Arto Math Biosci Article Mathematical epidemiology is a well-recognized discipline to model infectious diseases. It also provides guidance for public health officials to limit outbreaks. Nevertheless, epidemics take societies by surprise every now and then, for example, when the Ebola virus epidemic raged seemingly unrestrained in Western Africa. We provide insight to this capricious character of nature by describing the epidemic as a natural process, i.e., a phenomenon governed by thermodynamics. Our account, based on statistical mechanics of open systems, clarifies that it is impossible to predict accurately epidemic courses because everything depends on everything else. Nonetheless, the thermodynamic theory yields a comprehensive and analytical view of the epidemic. The tenet subsumes various processes in a scale-free manner from the molecular to the societal levels. The holistic view accentuates overarching procedures in arresting and eradicating epidemics. Elsevier Inc. 2018-05 2018-03-10 /pmc/articles/PMC7094378/ /pubmed/29534891 http://dx.doi.org/10.1016/j.mbs.2018.03.012 Text en © 2018 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Koivu-Jolma, Mikko
Annila, Arto
Epidemic as a natural process
title Epidemic as a natural process
title_full Epidemic as a natural process
title_fullStr Epidemic as a natural process
title_full_unstemmed Epidemic as a natural process
title_short Epidemic as a natural process
title_sort epidemic as a natural process
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7094378/
https://www.ncbi.nlm.nih.gov/pubmed/29534891
http://dx.doi.org/10.1016/j.mbs.2018.03.012
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