Strong convergence of the partially truncated Euler–Maruyama scheme for a stochastic age-structured SIR epidemic model
Yan Li,
Ming Ye and
Qimin Zhang
Applied Mathematics and Computation, 2019, vol. 362, issue C, -
Abstract:
we study in this paper strong convergence of the partially truncated Euler-Maruyama scheme for an age-structured Susceptible-Infected-Removed (SIR) epidemic model with environmental noise. Using the semigroup theory, the existence and uniqueness of global positive solution for the model is first proved. We then define a truncated function and develop a partially truncated EM numerical solutions to the stochastic age-structured SIR epidemic model. We present the pth moment boundedness of the partially truncated EM numerical approximate solutions under appropriate conditions. Furthermore, the strong Lq convergence is established for the condition of 2 ≤ q < p of the partially truncated EM scheme. Finally, numerical simulations and examples are provided to demonstrate theoretical results and to illustrate validity of the partially truncated EM scheme.
Keywords: Stochastic age-structured SIR epidemic model; Numerical solution; Partially truncated Euler-Maruyama scheme; Convergence (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300319304989
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:apmaco:v:362:y:2019:i:c:24
DOI: 10.1016/j.amc.2019.06.033
Access Statistics for this article
Applied Mathematics and Computation is currently edited by Theodore Simos
More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().