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Introduction to Group-Structured-Epidemic Model

The spread of an infectious disease in a population is a random process when considering a small group of individuals. However, to a great group of individuals, the use of deterministic behavior is better. Based on these facts, in the literature, there were proposed stochastic and deterministic epid...

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Detalles Bibliográficos
Autores principales: Dias, Samaherni, Queiroz, Kurios, Araujo, Aldayr
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8557951/
http://dx.doi.org/10.1007/s40313-021-00841-7
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author Dias, Samaherni
Queiroz, Kurios
Araujo, Aldayr
author_facet Dias, Samaherni
Queiroz, Kurios
Araujo, Aldayr
author_sort Dias, Samaherni
collection PubMed
description The spread of an infectious disease in a population is a random process when considering a small group of individuals. However, to a great group of individuals, the use of deterministic behavior is better. Based on these facts, in the literature, there were proposed stochastic and deterministic epidemic models. This work proposes a mixed compartmental epidemic model that allows stratifying the population into groups, considers demographic and environmental variability, presents an approximation to stochastic effects, and contemplates the network effects. The proposed model has a compact form to assist in the synthesis of the control law and parameters estimation strategies. Its objective is to overcome the difficulties encountered when used purely deterministic or purely stochastic models. In the end, to detail and verify the functioning of the proposed model, we present a set of flowcharts and simulations.
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spelling pubmed-85579512021-11-01 Introduction to Group-Structured-Epidemic Model Dias, Samaherni Queiroz, Kurios Araujo, Aldayr J Control Autom Electr Syst Article The spread of an infectious disease in a population is a random process when considering a small group of individuals. However, to a great group of individuals, the use of deterministic behavior is better. Based on these facts, in the literature, there were proposed stochastic and deterministic epidemic models. This work proposes a mixed compartmental epidemic model that allows stratifying the population into groups, considers demographic and environmental variability, presents an approximation to stochastic effects, and contemplates the network effects. The proposed model has a compact form to assist in the synthesis of the control law and parameters estimation strategies. Its objective is to overcome the difficulties encountered when used purely deterministic or purely stochastic models. In the end, to detail and verify the functioning of the proposed model, we present a set of flowcharts and simulations. Springer US 2021-10-31 2022 /pmc/articles/PMC8557951/ http://dx.doi.org/10.1007/s40313-021-00841-7 Text en © Brazilian Society for Automatics--SBA 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Dias, Samaherni
Queiroz, Kurios
Araujo, Aldayr
Introduction to Group-Structured-Epidemic Model
title Introduction to Group-Structured-Epidemic Model
title_full Introduction to Group-Structured-Epidemic Model
title_fullStr Introduction to Group-Structured-Epidemic Model
title_full_unstemmed Introduction to Group-Structured-Epidemic Model
title_short Introduction to Group-Structured-Epidemic Model
title_sort introduction to group-structured-epidemic model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8557951/
http://dx.doi.org/10.1007/s40313-021-00841-7
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