Dynamical analysis and optimal control of an SIVS epidemic model with nonmonotone incidence rate on complex network

被引:0
|
作者
Zhou, Yunsu [1 ]
Liu, Xianning [1 ]
Wei, Yangjiang [2 ]
机构
[1] Southwest Univ, Sch Math & Stat, Key Lab Ecoenvironm Three Gorges Reservoir Reg, Minist Educ, Chongqing 400715, Peoples R China
[2] Nanning Normal Univ, Sch Math & Stat, Nanning 530023, Peoples R China
基金
中国国家自然科学基金;
关键词
Scale-free network; Psychological effect; Imperfect vaccination; Optimal control; GLOBAL STABILITY; VACCINATION;
D O I
10.1016/j.cnsns.2024.108531
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
With epidemic outbreak, individuals are afraid of being infected, become cautious and adopt behavioral changes to reduce their probability of being infected especially at high infective level. This phenomenon is regarded as the psychological effect in the population, which occurs not only in the susceptible population but also in the vaccinated population. In this paper, considering the psychological effects of two populations, a new SIVS model with nonmonotone incidence rate and imperfect vaccination is constructed on the scale-free network, which is more closely related to the actual spread of epidemics. Based on the model, existence conditions of multiple endemic equilibrium points and two threshold parameters are firstly derived. Next, a necessary and sufficient condition which determines the occurrence of a backward bifurcation at R0 = 1 is obtained. Besides, the global asymptotical stability of disease-free equilibrium and the persistence of the disease are proved. By using the monotone iterative technique, the global attractivity of the unique endemic equilibrium is analyzed. And the optimal vaccinated strategy is studied by the method of Pontryagin's maximum principle. Finally, through numerical simulations, the interaction and impact of the psychological effects, vaccines, and disease outbreaks are revealed.
引用
收藏
页数:23
相关论文
共 50 条
  • [41] Global Dynamics of a Susceptible-Infectious-Recovered Epidemic Model with a Generalized Nonmonotone Incidence Rate
    Lu, Min
    Huang, Jicai
    Ruan, Shigui
    Yu, Pei
    JOURNAL OF DYNAMICS AND DIFFERENTIAL EQUATIONS, 2021, 33 (04) : 1625 - 1661
  • [42] A stochastic epidemic model with nonmonotone incidence rate: Sufficient and necessary conditions for near-optimality
    Guo, Wenjuan
    Zhang, Qimin
    Rong, Libin
    INFORMATION SCIENCES, 2018, 467 : 670 - 684
  • [43] GLOBAL DYNAMICS AND BIFURCATIONS IN A SIRS EPIDEMIC MODEL WITH A NONMONOTONE INCIDENCE RATE AND A PIECEWISE-SMOOTH TREATMENT RATE
    Pan, Qin
    Huang, Jicai
    Huang, Qihua
    DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES B, 2022, 27 (07): : 3533 - 3561
  • [44] Global dynamics of deterministic and stochastic epidemic systems with nonmonotone incidence rate
    Feng, Tao
    Qiu, Zhipeng
    INTERNATIONAL JOURNAL OF BIOMATHEMATICS, 2018, 11 (08)
  • [45] Reachability analysis and optimal control for epidemic spreading model on multiplex network
    Prakash, M. V. Surya
    Mahindrakar, Arun D.
    Pasumarthy, Ramkrishna
    2019 FIFTH INDIAN CONTROL CONFERENCE (ICC), 2019, : 383 - 388
  • [46] Optimal control and analysis of a stochastic SEIR epidemic model with nonlinear incidence and treatment
    Du, Jinji
    Qin, Chuangliang
    Hui, Yuanxian
    AIMS MATHEMATICS, 2024, 9 (12): : 33532 - 33550
  • [47] Epidemic spreading model of complex dynamical network with the heterogeneity of nodes
    Hong, Sheng
    Yang, Hongqi
    Zhao, Tingdi
    Ma, Xiaomin
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2016, 47 (11) : 2745 - 2752
  • [48] Stability of the Equilibria in a Discrete-Time Sivs Epidemic Model with Standard Incidence
    Parsamanesh, Mahmood
    Mehrshad, Saeed
    FILOMAT, 2019, 33 (08) : 2393 - 2408
  • [49] Global stability analysis of an epidemic model with feedback control and general incidence rate
    Wang, Lin-Lin
    Fan, Yong-Hong
    INTERNATIONAL JOURNAL OF BIOMATHEMATICS, 2024,
  • [50] Dynamical analysis and optimal control for a malware propagation model in an information network
    Zhu, Linhe
    Zhao, Hongyong
    NEUROCOMPUTING, 2015, 149 : 1370 - 1386