Numerical analysis of a reaction-diffusion susceptible-infected-susceptible epidemic model

被引:6
|
作者
Liu, X. [1 ]
Yang, Z. W. [2 ]
机构
[1] Liaocheng Univ, Sch Math Sci, Liaocheng 252059, Shandong, Peoples R China
[2] Harbin Inst Technol, Sch Math, Harbin 150001, Peoples R China
来源
COMPUTATIONAL & APPLIED MATHEMATICS | 2022年 / 41卷 / 08期
关键词
Reaction-diffusion SIS model; Numerical solution; Convergence; Long-time behaviors; BASIC REPRODUCTION NUMBER; QUALITATIVE-ANALYSIS; ASYMPTOTIC PROFILES; STEADY-STATES; STABILITY; BEHAVIOR;
D O I
10.1007/s40314-022-02113-9
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper presents the numerical properties of a reaction-diffusion susceptible-infected-susceptible epidemic model. Comparing with existing literature, our numerical scheme gains advantage in terms of preserving the biological meanings (such as positivity or invariance of total population) unconditionally. An implicit-explicit technique is implemented in the time integration, which ensures the numerical positivity without CFL conditions while reducing the computation complexity. The solvability, convergence in finite time and the long-time behaviors of numerical solutions are investigated. A threshold value R-0(Delta x) for the long-time dynamics of numerical solutions is proposed, which is named as a numerical basic reproduction number. It is proved that the numerical disease-free equilibrium is locally asymptotically stable if R-0(Delta x) < 1 and unstable if R-0(Delta x) > 1. It is presented that R-0(Delta x) shares the same monotonicity and limits as the basic reproduction number of the underlying model and converges to the exact one. Some numerical experiments are given in the end to confirm the conclusions and explore the stability of the endemic equilibrium.
引用
收藏
页数:26
相关论文
共 50 条
  • [31] Flight Delay Propagation Analysis Based on the Mechanism of the Susceptible-Infected-Susceptible Model
    Wu, Weiwei
    Zhang, Haoyu
    Zhu, Jinfu
    Witlox, Frank
    INFORMATION TECHNOLOGY AND INTELLIGENT TRANSPORTATION SYSTEMS (ITITS 2017), 2017, 296 : 180 - 192
  • [32] Susceptible-Infected-Susceptible Epidemic Discrete Dynamic System Based on Tsallis Entropy
    Momani, Shaher
    Ibrahim, Rabha W.
    Hadid, Samir B.
    ENTROPY, 2020, 22 (07)
  • [33] Strong ties promote the epidemic prevalence in susceptible-infected-susceptible spreading dynamics
    Cui, Ai-Xiang
    Yang, Zimo
    Zhou, Tao
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2016, 445 : 335 - 342
  • [34] Epidemic threshold of node-weighted susceptible-infected-susceptible models on networks
    Wu, Qingchu
    Zhang, Haifeng
    JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL, 2016, 49 (34)
  • [35] Coordination of a Dual-Channel Pharmaceutical Supply Chain Based on the Susceptible-Infected-Susceptible Epidemic Model
    Hou, Yanhong
    Wang, Fan
    Chen, Zhitong
    Shi, Victor
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2020, 17 (09)
  • [36] Second-order mean-field susceptible-infected-susceptible epidemic threshold
    Cator, E.
    Van Mieghem, P.
    PHYSICAL REVIEW E, 2012, 85 (05):
  • [37] Modeling computer virus prevalence with a susceptible-infected-susceptible model with reintroduction
    Wierman, JC
    Marchette, DJ
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2004, 45 (01) : 3 - 23
  • [38] Autocorrelation of the susceptible-infected-susceptible process on networks
    Liu, Qiang
    Van Mieghem, Piet
    PHYSICAL REVIEW E, 2018, 97 (06)
  • [39] Long-term dynamics of a q-deformed discrete susceptible-infected-susceptible epidemic model with delay
    Salman, Sanaa Moussa
    PRAMANA-JOURNAL OF PHYSICS, 2019, 92 (05):
  • [40] Susceptible-Infected-Susceptible Dynamics with Mitigation in Connection of Infected Population
    Kim, K. M.
    Dias, C.
    Hase, M. O.
    BRAZILIAN JOURNAL OF PHYSICS, 2023, 53 (04)