Version 1
: Received: 2 September 2023 / Approved: 5 September 2023 / Online: 5 September 2023 (03:47:46 CEST)
How to cite:
Alsammani, A. Stochastic modeling and computational simulations of HBV infection dynamics. Preprints2023, 2023090222. https://doi.org/10.20944/preprints202309.0222.v1
Alsammani, A. Stochastic modeling and computational simulations of HBV infection dynamics. Preprints 2023, 2023090222. https://doi.org/10.20944/preprints202309.0222.v1
Alsammani, A. Stochastic modeling and computational simulations of HBV infection dynamics. Preprints2023, 2023090222. https://doi.org/10.20944/preprints202309.0222.v1
APA Style
Alsammani, A. (2023). Stochastic modeling and computational simulations of HBV infection dynamics. Preprints. https://doi.org/10.20944/preprints202309.0222.v1
Chicago/Turabian Style
Alsammani, A. 2023 "Stochastic modeling and computational simulations of HBV infection dynamics" Preprints. https://doi.org/10.20944/preprints202309.0222.v1
Abstract
This study investigates the stochastic dynamics of hepatitis B virus (HBV) infection using a newly proposed stochastic model. Contrary to deterministic models that fail to encapsulate the inherent randomness and fluctuations in biological processes, our stochastic model provides a more realistic representation of HBV infection dynamics. It incorporates random variability, thereby acknowledging the changes in viral and cellular populations and uncertainties in parameters such as infection rates and immune responses. We examine the solution's existence, uniqueness, and positivity for the proposed model, followed by a comprehensive stability analysis. We provide the necessary and sufficient conditions for local and global stability, offering deep insight into the infection dynamics. Furthermore, we utilize numerical simulations to corroborate our theoretical results. This research provides a robust tool for understanding the complex behavior of HBV dynamics, contributing significantly to the ongoing quest for more effective HBV control and prevention strategies.
Keywords
Stochastic dynamics; HBV; stability in probability; Euler-Maruyama; Milstein
Subject
Computer Science and Mathematics, Mathematical and Computational Biology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
