The balanced implicit method of preserving positivity for the stochastic SIQS epidemic model

Yan Li and Qimin Zhang

Physica A: Statistical Mechanics and its Applications, 2020, vol. 538, issue C

Abstract: The main purpose of this paper is to develop a numerical method preserving positivity for a stochastic SIQS epidemic model which is an effective tactics for forecasting and controlling infectious diseases. By the explicit Euler–Maruyama (EM) scheme, we can obtain a numerical approximate solution of the stochastic SIQS epidemic model. We will explore the convergence property of the EM approximate solution to the true solution. However, the explicit EM scheme has it own defection because of the influence of environmental fluctuation, it may not preserve positivity of numerical solution. Therefore, we will construct a balanced implicit numerical method which motivated by Schurz in Schurz (1996). It is confirmed that the Balanced Implicit Method (BIM) can preserve positivity. We prove that the BIM approximate solution will converge to the true solution. By numerical simulations to verify the positivity of solution and the efficiency of our proposed numerical method.

Keywords: SIQS epidemic model; Numerical solution; Balanced implicit method; Convergence (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437119316826
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

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:phsmap:v:538:y:2020:i:c:s0378437119316826

DOI: 10.1016/j.physa.2019.122972

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().