Domain preserving and strongly converging explicit scheme for the stochastic SIS epidemic model

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-08-22 DOI:10.1016/j.cam.2024.116219
Yiannis Kiouvrekis , Ioannis S. Stamatiou
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引用次数: 0

Abstract

In this article, we construct a numerical method for a stochastic version of the Susceptible–Infected–Susceptible (SIS) epidemic model, expressed by a suitable stochastic differential equation (SDE), by using the semi-discrete method to a suitable transformed process. We prove the strong convergence of the proposed method, with order 1, and examine its stability properties. Since SDEs generally lack analytical solutions, numerical techniques are commonly employed. Hence, the research will seek numerical solutions for existing stochastic models by constructing suitable numerical schemes and comparing them with other schemes. The objective is to achieve a qualitative and efficient approach to solving the equations. Additionally, for models that have not yet been proposed for stochastic modeling using SDEs, the research will formulate them appropriately, conduct theoretical analysis of the model properties, and subsequently solve the corresponding SDEs.

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随机 SIS 流行病模型的保域和强收敛显式方案
在本文中,我们通过对合适的变换过程使用半离散方法,为由合适的随机微分方程(SDE)表示的随机版易感-感染-易感(SIS)流行病模型构建了一种数值方法。我们证明了所提方法的强收敛性(阶次为 1),并检验了其稳定性。由于 SDE 通常缺乏解析解,因此通常采用数值技术。因此,本研究将通过构建合适的数值方案并与其他方案进行比较,为现有的随机模型寻求数值解。目的是实现定性和高效的方程求解方法。此外,对于尚未提出使用 SDE 进行随机建模的模型,研究将对其进行适当表述,对模型特性进行理论分析,然后求解相应的 SDE。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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