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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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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1721389227185274880 |