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ISSN:2164-6457 (print)
ISSN:2164-6473 (online)
Journal of Applied Nonlinear Dynamics
Miguel A. F. Sanjuan (editor), Albert C.J. Luo (editor)
Miguel A. F. Sanjuan (editor)

Department of Physics, Universidad Rey Juan Carlos, 28933 Mostoles, Madrid, Spain

Email: miguel.sanjuan@urjc.es

Albert C.J. Luo (editor)

Department of Mechanical and Industrial Engineering, Southern Illinois University Ed-wardsville, IL 62026-1805, USA

Fax: +1 618 650 2555 Email: aluo@siue.edu

Understanding HCV through the Lens of Mathematical Modeling: A Comprehensive Review

Journal of Applied Nonlinear Dynamics 13(4) (2024) 761--780 | DOI:10.5890/JAND.2024.12.010

Bikash Kumar, Manoranjan K Singh, Debnarayan Khatua, Anupam De

Department of Mathematics, Magadh University, Bodh Gaya, Bihar, 824234, India

Department of Humanities and Sciences, Vignan's Foundation for Science, Technology and Research (Deemed to be University), Guntur, A.P., 522213, India

School of Applied Sciences and Humanities, Haldia Institute of Technology, Haldia, West Bengal, 721657, India

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Abstract

The World Health Organization announced worldwide hepatitis C virus (HCV) eradication goals in 2016, including an 80\% decrease in HCV transmission by 2030. People who inject the drug (PWID) are responsible for most of the new HCV infections.Hence, elimination initiatives must pay special attention to this group. Mathematical modeling can provide important information on the level and goals of intervention, which is urgently needed because governments seek guidance to eliminate PWID. A thorough assessment of the state of the mathematical modelling of hepatitis C virus (HCV) infection is given in this article. The article starts by reviewing HCV's fundamental biology and the difficulties in understanding the virus. The paper then focuses on the numerous mathematical models created to investigate various facets of HCV infection, such as viral dynamics, host-virus interactions, and therapeutic results. The review also discusses the most recent developments in systems biology and how they relate to the investigation of HCV. The study provides important insights into the dynamics of HCV-HIV coinfection and highlights the need for integrated approaches to prevent and manage the two infections. Mathematical modelling allows the analysis to simulate complex biological systems and predict disease. The focus on HCV-HIV coinfection provides a valuable perspective on the interplay between the two viruses. The article's conclusion discusses the possible advantages of a multidisciplinary approach for comprehending the intricate interactions between the virus and the host and future opportunities for mathematical modelling of HCV.

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