In Vivo HIV Dynamics, Modeling the Interaction of HIV and Immune System via Non-Integer Derivatives

Author:

Jan Asif1,Srivastava Hari Mohan2345ORCID,Khan Amin6ORCID,Mohammed Pshtiwan Othman7ORCID,Jan Rashid6ORCID,Hamed Y. S.8ORCID

Affiliation:

1. Department of Pathogenic Microbiology & Immunology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, 76 West Yanta Road, Xi’an 710061, China

2. Department of Mathematics and Statistics, University of Victoria, Victoria, BC V8W 3R4, Canada

3. Department of Mathematics and Informatics, Azerbaijan University, 71 Jeyhun Hajibeyli Street, AZ1007 Baku, Azerbaijan

4. Center for Converging Humanities, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea

5. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 40402, Taiwan

6. Department of Mathematics, University of Swabi, Swabi 23561, KPK, Pakistan

7. Department of Mathematics, College of Education, University of Sulaimani, Sulaimani 46001, Iraq

8. Department of Mathematics and Statistics, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia

Abstract

The economic burden of HIV extends beyond the individual level and affects communities and countries. HIV can lead to decreased economic growth due to lost productivity and increased healthcare costs. In some countries, the HIV epidemic has led to a reduction in life expectancy, which can impact the overall quality of life and economic prosperity. Therefore, it is significant to investigate the intricate dynamics of this viral infection to know how the virus interacts with the immune system. In the current research, we will formulate the dynamics of HIV infection in the host body to conceptualize the interaction of T-cells and the immune system. The recommended model of HIV infection is presented with the help of fractional calculus for more precious outcomes. We introduce numerical methods to demonstrate how the input parameters affect the output of the system. The dynamical behavior and chaotic nature of the system are visualized with the variation of different input factors. The system’s tracking path has been numerically depicted and the impact of the viruses on T-cells has been demonstrated. In addition to this, the key factors of the system has been predicted through numerical findings. Our results predict that the strong non-linearity of the system is responsible for the chaos and oscillation, which are so closely related. The chaotic parameters of the system are highlighted and are recommended for the control of the chaos of the system.

Publisher

MDPI AG

Subject

Statistics and Probability,Statistical and Nonlinear Physics,Analysis

Reference28 articles.

1. Stochastic Model for In-Host HIV Dynamics with Therapeutic Intervention;Mbogo;Int. Sch. Res. Not.,2013

2. (2011). United Nations International Children’s Emergency Fund, Joint United Nations Programme on HIV and AIDS and World Health Organization (2011) Global HIV/ AIDS Response: Epidemic Update and Health Sector Progress towards Universal Access: Progress Report 2011, World Health Organization.

3. World Health Organization (2010). World Health Statistics 2010, World Health Organization.

4. Analysis and Simulation of the Three-Component Model of HIV Dynamics;Jones;SIAM Undergrad. Res. Online,2013

5. HIV Dynamics: Modeling, Data Analysis, and Optimal Treatment Protocols;Adams;J. Comput. Appl. Math.,2015

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