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Fractional SIR epidemiological models

The purpose of this work is to make a case for epidemiological models with fractional exponent in the contribution of sub-populations to the incidence rate. More specifically, we question the standard assumption in the literature on epidemiological models, where the incidence rate dictating propagat...

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Autores principales: Taghvaei, Amirhossein, Georgiou, Tryphon T., Norton, Larry, Tannenbaum, Allen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7705759/
https://www.ncbi.nlm.nih.gov/pubmed/33257790
http://dx.doi.org/10.1038/s41598-020-77849-7
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author Taghvaei, Amirhossein
Georgiou, Tryphon T.
Norton, Larry
Tannenbaum, Allen
author_facet Taghvaei, Amirhossein
Georgiou, Tryphon T.
Norton, Larry
Tannenbaum, Allen
author_sort Taghvaei, Amirhossein
collection PubMed
description The purpose of this work is to make a case for epidemiological models with fractional exponent in the contribution of sub-populations to the incidence rate. More specifically, we question the standard assumption in the literature on epidemiological models, where the incidence rate dictating propagation of infections is taken to be proportional to the product between the infected and susceptible sub-populations; a model that relies on strong mixing between the two groups and widespread contact between members of the groups. We contend, that contact between infected and susceptible individuals, especially during the early phases of an epidemic, takes place over a (possibly diffused) boundary between the respective sub-populations. As a result, the rate of transmission depends on the product of fractional powers instead. The intuition relies on the fact that infection grows in geographically concentrated cells, in contrast to the standard product model that relies on complete mixing of the susceptible to infected sub-populations. We validate the hypothesis of fractional exponents (1) by numerical simulation for disease propagation in graphs imposing a local structure to allowed disease transmissions and (2) by fitting the model to the JHU CSSE COVID-19 Data for the period Jan-22-20 to April-30-20, for the countries of Italy, Germany, France, and Spain.
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spelling pubmed-77057592020-12-02 Fractional SIR epidemiological models Taghvaei, Amirhossein Georgiou, Tryphon T. Norton, Larry Tannenbaum, Allen Sci Rep Article The purpose of this work is to make a case for epidemiological models with fractional exponent in the contribution of sub-populations to the incidence rate. More specifically, we question the standard assumption in the literature on epidemiological models, where the incidence rate dictating propagation of infections is taken to be proportional to the product between the infected and susceptible sub-populations; a model that relies on strong mixing between the two groups and widespread contact between members of the groups. We contend, that contact between infected and susceptible individuals, especially during the early phases of an epidemic, takes place over a (possibly diffused) boundary between the respective sub-populations. As a result, the rate of transmission depends on the product of fractional powers instead. The intuition relies on the fact that infection grows in geographically concentrated cells, in contrast to the standard product model that relies on complete mixing of the susceptible to infected sub-populations. We validate the hypothesis of fractional exponents (1) by numerical simulation for disease propagation in graphs imposing a local structure to allowed disease transmissions and (2) by fitting the model to the JHU CSSE COVID-19 Data for the period Jan-22-20 to April-30-20, for the countries of Italy, Germany, France, and Spain. Nature Publishing Group UK 2020-11-30 /pmc/articles/PMC7705759/ /pubmed/33257790 http://dx.doi.org/10.1038/s41598-020-77849-7 Text en © The Author(s) 2020 Open AccessThis 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/.
spellingShingle Article
Taghvaei, Amirhossein
Georgiou, Tryphon T.
Norton, Larry
Tannenbaum, Allen
Fractional SIR epidemiological models
title Fractional SIR epidemiological models
title_full Fractional SIR epidemiological models
title_fullStr Fractional SIR epidemiological models
title_full_unstemmed Fractional SIR epidemiological models
title_short Fractional SIR epidemiological models
title_sort fractional sir epidemiological models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7705759/
https://www.ncbi.nlm.nih.gov/pubmed/33257790
http://dx.doi.org/10.1038/s41598-020-77849-7
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