Explicit numerical approximation for an impulsive stochastic age-structured HIV infection model with Markovian switching

Wenjuan Guo and Qimin Zhang

Mathematics and Computers in Simulation (MATCOM), 2021, vol. 182, issue C, 86-115

Abstract: This paper considers an impulsive switching human immunodeficiency virus (HIV) infection model incorporating the mean-reverting Ornstein–Uhlenbeck process. The model involve the virus-to-cell infection and cell-to-cell transmission and has an explicit age-dependent structure. Due to the exact solution of this system cannot be expressed explicitly, it is necessary to give a suitable numerical method to discuss the numerical solution. In this paper, we apply the truncated Euler–Maruyama (EM) method to investigate the explicit numerical approximation for the impulsive stochastic age-structured HIV infection model with Markovian switching. We study the pth moment boundedness of the numerical solution, and the corresponding strong convergence of such algorithm. Numerical simulations are presented to demonstrate the validity of our findings.

Keywords: Stochastic HIV model; Age-structured; Impulse effects; Markovian switching; Explicit EM method; Strong convergence (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475420303554
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:182:y:2021:i:c:p:86-115

DOI: 10.1016/j.matcom.2020.10.015

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().