Numerical investigations of stochastic HIV/AIDS infection model

In this paper, a stochastic HIV/AIDS epidemic model has been studied numerically. A discussion among the solutions related to deterministic HIV/AIDS model and stochastic HIV/ AIDS epidemic model has shown that the stochastic solution is more realistic than the deterministic solution. To control the...

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Main Authors: Zain Ul Abadin Zafar, Nigar Ali, Samina Younas, Sayed F. Abdelwahab, Kottakkaran Sooppy Nisar
Format: Article
Language:English
Published: Elsevier 2021-12-01
Series:Alexandria Engineering Journal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016821002696
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spelling doaj-ee1f6773df854ba88e6653f24b25b0792021-06-09T05:49:55ZengElsevierAlexandria Engineering Journal1110-01682021-12-0160653415363Numerical investigations of stochastic HIV/AIDS infection modelZain Ul Abadin Zafar0Nigar Ali1Samina Younas2Sayed F. Abdelwahab3Kottakkaran Sooppy Nisar4Department of Mathematics, Faculty of Sciences, University of Central Punjab, Lahore, PakistanDepartment of Mathematics, University of Malakand, Chakdara, PakistanDepartment of Zoology, Government College University, Lahore, PakistanDepartment of Pharmaceutics and Industrial Pharmacy, College of Pharmacy, Taif University, P.O. Box 11099, Taif 21944, Saudi ArabiaDepartment of Mathematics, College of Arts and Sciences, Wadi Aldawaser, Prince Sattam bin Abdulaziz University, Saudi Arabia; Corresponding author.In this paper, a stochastic HIV/AIDS epidemic model has been studied numerically. A discussion among the solutions related to deterministic HIV/AIDS model and stochastic HIV/ AIDS epidemic model has shown that the stochastic solution is more realistic than the deterministic solution. To control the diseases, the threshold parameter R0 plays a key role in the stochastic HIV/AIDS epidemic model. If R0<1 then disease is under control while the disease is out of control if R0>1. The explicit approaches such as the Milstein scheme, stochastic Euler scheme, and stochastic Runge-Kutta 4 are dependent on temporal step size, whereas non-standard finite difference approaches are independent of step size. The results for numerical approaches like the Milstein scheme, stochastic Euler scheme, and stochastic Runge-Kutta 4 scheme fail for outsized step size. The stochastic non-standard finite difference scheme conserves dynamic features like confinedness, consistency and positivity.http://www.sciencedirect.com/science/article/pii/S1110016821002696HIV/AIDS epidemic modelStochastic differential equations (SDEs)Milstein schemeStochastic NSFD scheme (SNSFD)Stochastic Euler scheme (SES)Stochastic Runge-Kutta 4 (SRK-4) scheme
collection DOAJ
language English
format Article
sources DOAJ
author Zain Ul Abadin Zafar
Nigar Ali
Samina Younas
Sayed F. Abdelwahab
Kottakkaran Sooppy Nisar
spellingShingle Zain Ul Abadin Zafar
Nigar Ali
Samina Younas
Sayed F. Abdelwahab
Kottakkaran Sooppy Nisar
Numerical investigations of stochastic HIV/AIDS infection model
Alexandria Engineering Journal
HIV/AIDS epidemic model
Stochastic differential equations (SDEs)
Milstein scheme
Stochastic NSFD scheme (SNSFD)
Stochastic Euler scheme (SES)
Stochastic Runge-Kutta 4 (SRK-4) scheme
author_facet Zain Ul Abadin Zafar
Nigar Ali
Samina Younas
Sayed F. Abdelwahab
Kottakkaran Sooppy Nisar
author_sort Zain Ul Abadin Zafar
title Numerical investigations of stochastic HIV/AIDS infection model
title_short Numerical investigations of stochastic HIV/AIDS infection model
title_full Numerical investigations of stochastic HIV/AIDS infection model
title_fullStr Numerical investigations of stochastic HIV/AIDS infection model
title_full_unstemmed Numerical investigations of stochastic HIV/AIDS infection model
title_sort numerical investigations of stochastic hiv/aids infection model
publisher Elsevier
series Alexandria Engineering Journal
issn 1110-0168
publishDate 2021-12-01
description In this paper, a stochastic HIV/AIDS epidemic model has been studied numerically. A discussion among the solutions related to deterministic HIV/AIDS model and stochastic HIV/ AIDS epidemic model has shown that the stochastic solution is more realistic than the deterministic solution. To control the diseases, the threshold parameter R0 plays a key role in the stochastic HIV/AIDS epidemic model. If R0<1 then disease is under control while the disease is out of control if R0>1. The explicit approaches such as the Milstein scheme, stochastic Euler scheme, and stochastic Runge-Kutta 4 are dependent on temporal step size, whereas non-standard finite difference approaches are independent of step size. The results for numerical approaches like the Milstein scheme, stochastic Euler scheme, and stochastic Runge-Kutta 4 scheme fail for outsized step size. The stochastic non-standard finite difference scheme conserves dynamic features like confinedness, consistency and positivity.
topic HIV/AIDS epidemic model
Stochastic differential equations (SDEs)
Milstein scheme
Stochastic NSFD scheme (SNSFD)
Stochastic Euler scheme (SES)
Stochastic Runge-Kutta 4 (SRK-4) scheme
url http://www.sciencedirect.com/science/article/pii/S1110016821002696
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AT nigarali numericalinvestigationsofstochastichivaidsinfectionmodel
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AT sayedfabdelwahab numericalinvestigationsofstochastichivaidsinfectionmodel
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