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Fractional Stochastic Differential Equation Approach for Spreading of Diseases

The nonlinear fractional stochastic differential equation approach with Hurst parameter H within interval [Formula: see text] to study the time evolution of the number of those infected by the coronavirus in countries where the number of cases is large as Brazil is studied. The rises and falls of no...

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Autor principal: Lima, Leonardo dos Santos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140412/
https://www.ncbi.nlm.nih.gov/pubmed/35626602
http://dx.doi.org/10.3390/e24050719
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author Lima, Leonardo dos Santos
author_facet Lima, Leonardo dos Santos
author_sort Lima, Leonardo dos Santos
collection PubMed
description The nonlinear fractional stochastic differential equation approach with Hurst parameter H within interval [Formula: see text] to study the time evolution of the number of those infected by the coronavirus in countries where the number of cases is large as Brazil is studied. The rises and falls of novel cases daily or the fluctuations in the official data are treated as a random term in the stochastic differential equation for the fractional Brownian motion. The projection of novel cases in the future is treated as quadratic mean deviation in the official data of novel cases daily since the beginning of the pandemic up to the present. Moreover, the rescaled range analysis (RS) is employed to determine the Hurst index for the time series of novel cases and some statistical tests are performed with the aim to determine the shape of the probability density of novel cases in the future.
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spelling pubmed-91404122022-05-28 Fractional Stochastic Differential Equation Approach for Spreading of Diseases Lima, Leonardo dos Santos Entropy (Basel) Article The nonlinear fractional stochastic differential equation approach with Hurst parameter H within interval [Formula: see text] to study the time evolution of the number of those infected by the coronavirus in countries where the number of cases is large as Brazil is studied. The rises and falls of novel cases daily or the fluctuations in the official data are treated as a random term in the stochastic differential equation for the fractional Brownian motion. The projection of novel cases in the future is treated as quadratic mean deviation in the official data of novel cases daily since the beginning of the pandemic up to the present. Moreover, the rescaled range analysis (RS) is employed to determine the Hurst index for the time series of novel cases and some statistical tests are performed with the aim to determine the shape of the probability density of novel cases in the future. MDPI 2022-05-17 /pmc/articles/PMC9140412/ /pubmed/35626602 http://dx.doi.org/10.3390/e24050719 Text en © 2022 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lima, Leonardo dos Santos
Fractional Stochastic Differential Equation Approach for Spreading of Diseases
title Fractional Stochastic Differential Equation Approach for Spreading of Diseases
title_full Fractional Stochastic Differential Equation Approach for Spreading of Diseases
title_fullStr Fractional Stochastic Differential Equation Approach for Spreading of Diseases
title_full_unstemmed Fractional Stochastic Differential Equation Approach for Spreading of Diseases
title_short Fractional Stochastic Differential Equation Approach for Spreading of Diseases
title_sort fractional stochastic differential equation approach for spreading of diseases
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140412/
https://www.ncbi.nlm.nih.gov/pubmed/35626602
http://dx.doi.org/10.3390/e24050719
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