Cargando…

Breakdown of a Nonlinear Stochastic Nipah Virus Epidemic Models through Efficient Numerical Methods

Background: Nipah virus (NiV) is a zoonotic virus (transmitted from animals to humans), which can also be transmitted through contaminated food or directly between people. According to a World Health Organization (WHO) report, the transmission of Nipah virus infection varies from animals to humans o...

Descripción completa

Detalles Bibliográficos
Autores principales: Raza, Ali, Awrejcewicz, Jan, Rafiq, Muhammad, Mohsin, Muhammad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8700744/
https://www.ncbi.nlm.nih.gov/pubmed/34945894
http://dx.doi.org/10.3390/e23121588
_version_ 1784620831400263680
author Raza, Ali
Awrejcewicz, Jan
Rafiq, Muhammad
Mohsin, Muhammad
author_facet Raza, Ali
Awrejcewicz, Jan
Rafiq, Muhammad
Mohsin, Muhammad
author_sort Raza, Ali
collection PubMed
description Background: Nipah virus (NiV) is a zoonotic virus (transmitted from animals to humans), which can also be transmitted through contaminated food or directly between people. According to a World Health Organization (WHO) report, the transmission of Nipah virus infection varies from animals to humans or humans to humans. The case fatality rate is estimated at 40% to 75%. The most infected regions include Cambodia, Ghana, Indonesia, Madagascar, the Philippines, and Thailand. The Nipah virus model is categorized into four parts: susceptible (S), exposed (E), infected (I), and recovered (R). Methods: The structural properties such as dynamical consistency, positivity, and boundedness are the considerable requirements of models in these fields. However, existing numerical methods like Euler–Maruyama and Stochastic Runge–Kutta fail to explain the main features of the biological problems. Results: The proposed stochastic non-standard finite difference (NSFD) employs standard and non-standard approaches in the numerical solution of the model, with positivity and boundedness as the characteristic determinants for efficiency and low-cost approximations. While the results from the existing standard stochastic methods converge conditionally or diverge in the long run, the solution by the stochastic NSFD method is stable and convergent over all time steps. Conclusions: The stochastic NSFD is an efficient, cost-effective method that accommodates all the desired feasible properties.
format Online
Article
Text
id pubmed-8700744
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-87007442021-12-24 Breakdown of a Nonlinear Stochastic Nipah Virus Epidemic Models through Efficient Numerical Methods Raza, Ali Awrejcewicz, Jan Rafiq, Muhammad Mohsin, Muhammad Entropy (Basel) Article Background: Nipah virus (NiV) is a zoonotic virus (transmitted from animals to humans), which can also be transmitted through contaminated food or directly between people. According to a World Health Organization (WHO) report, the transmission of Nipah virus infection varies from animals to humans or humans to humans. The case fatality rate is estimated at 40% to 75%. The most infected regions include Cambodia, Ghana, Indonesia, Madagascar, the Philippines, and Thailand. The Nipah virus model is categorized into four parts: susceptible (S), exposed (E), infected (I), and recovered (R). Methods: The structural properties such as dynamical consistency, positivity, and boundedness are the considerable requirements of models in these fields. However, existing numerical methods like Euler–Maruyama and Stochastic Runge–Kutta fail to explain the main features of the biological problems. Results: The proposed stochastic non-standard finite difference (NSFD) employs standard and non-standard approaches in the numerical solution of the model, with positivity and boundedness as the characteristic determinants for efficiency and low-cost approximations. While the results from the existing standard stochastic methods converge conditionally or diverge in the long run, the solution by the stochastic NSFD method is stable and convergent over all time steps. Conclusions: The stochastic NSFD is an efficient, cost-effective method that accommodates all the desired feasible properties. MDPI 2021-11-27 /pmc/articles/PMC8700744/ /pubmed/34945894 http://dx.doi.org/10.3390/e23121588 Text en © 2021 by the authors. 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
Raza, Ali
Awrejcewicz, Jan
Rafiq, Muhammad
Mohsin, Muhammad
Breakdown of a Nonlinear Stochastic Nipah Virus Epidemic Models through Efficient Numerical Methods
title Breakdown of a Nonlinear Stochastic Nipah Virus Epidemic Models through Efficient Numerical Methods
title_full Breakdown of a Nonlinear Stochastic Nipah Virus Epidemic Models through Efficient Numerical Methods
title_fullStr Breakdown of a Nonlinear Stochastic Nipah Virus Epidemic Models through Efficient Numerical Methods
title_full_unstemmed Breakdown of a Nonlinear Stochastic Nipah Virus Epidemic Models through Efficient Numerical Methods
title_short Breakdown of a Nonlinear Stochastic Nipah Virus Epidemic Models through Efficient Numerical Methods
title_sort breakdown of a nonlinear stochastic nipah virus epidemic models through efficient numerical methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8700744/
https://www.ncbi.nlm.nih.gov/pubmed/34945894
http://dx.doi.org/10.3390/e23121588
work_keys_str_mv AT razaali breakdownofanonlinearstochasticnipahvirusepidemicmodelsthroughefficientnumericalmethods
AT awrejcewiczjan breakdownofanonlinearstochasticnipahvirusepidemicmodelsthroughefficientnumericalmethods
AT rafiqmuhammad breakdownofanonlinearstochasticnipahvirusepidemicmodelsthroughefficientnumericalmethods
AT mohsinmuhammad breakdownofanonlinearstochasticnipahvirusepidemicmodelsthroughefficientnumericalmethods