The SAITS epidemic spreading model and its combinational optimal suppression control

被引:0
作者
Ding, Wei [1 ]
Ding, Li [1 ]
Kong, Zhengmin [1 ]
Liu, Feng [2 ]
机构
[1] Wuhan Univ, Sch Elect Engn & Automat, Wuhan 430072, Peoples R China
[2] Stevens Inst Technol, Sch Syst & Enterprises, Hoboken, NJ 07030 USA
基金
中国国家自然科学基金;
关键词
SAITS model; complex network; epidemic spreading; optimal control;
D O I
10.3934/mbe.2023157
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In this paper, an SAITS epidemic model based on a single layer static network is proposed and investigated. This model considers a combinational suppression control strategy to suppress the spread of epidemics, which includes transferring more individuals to compartments with low infection rate and with high recovery rate. The basic reproduction number of this model is calculated and the disease-free and endemic equilibrium points are discussed. An optimal control problem is formulated to minimize the number of infections with limited resources. The suppression control strategy is inves-tigated and a general expression for the optimal solution is given based on the Pontryagin's principle of extreme value. The validity of the theoretical results is verified by numerical simulations and Monte Carlo simulations.
引用
收藏
页码:3342 / 3354
页数:13
相关论文
共 23 条
  • [1] Modelling lockdown measures in epidemic outbreaks using selective socio-economic containment with uncertainty
    Albi, Giacomo
    Pareschi, Lorenzo
    Zanella, Mattia
    [J]. MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2021, 18 (06) : 7161 - 7190
  • [2] Control with uncertain data of socially structured compartmental epidemic models
    Albi, Giacomo
    Pareschi, Lorenzo
    Zanella, Mattia
    [J]. JOURNAL OF MATHEMATICAL BIOLOGY, 2021, 82 (07)
  • [3] Alsheri A. S., 2022, ALEX ENG J, V61, P6843, DOI [DOI 10.1016/j.aej.2021.12.0331110-0168, 10.1016/j.aej.2021.12.033]
  • [4] Epidemic thresholds in real networks
    Chakrabarti, Deepayan
    Wang, Yang
    Wang, Chenxi
    Leskovec, Jurij
    Faloutsos, Christos
    [J]. ACM TRANSACTIONS ON INFORMATION AND SYSTEM SECURITY, 2008, 10 (04)
  • [5] Chinazzi M, 2020, SCIENCE, V368, P395, DOI [10.1126/science.aba9757, 10.1101/2020.02.09.20021261]
  • [6] Evaluation of the effect of different policies in the containment of epidemic spreads for the COVID-19 case
    Di Giamberardino, Paolo
    Iacoviello, Daniela
    [J]. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2021, 65 (65)
  • [7] Network inference from population-level observation of epidemics
    Di Lauro, F.
    Croix, J. -C.
    Dashti, M.
    Berthouze, L.
    Kiss, I. Z.
    [J]. SCIENTIFIC REPORTS, 2020, 10 (01)
  • [8] Optimal control of epidemic spreading in the presence of social heterogeneity
    Dimarco, G.
    Toscani, G.
    Zanella, M.
    [J]. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2022, 380 (2224):
  • [9] Effect of information spreading to suppress the disease contagion on the epidemic vaccination game
    Kabir, K. M. Ariful
    Kuga, Kazuki
    Tanimoto, Jun
    [J]. CHAOS SOLITONS & FRACTALS, 2019, 119 : 180 - 187
  • [10] Optimal control of infectious disease: Information-induced vaccination and limited treatment
    Kumar, Anuj
    Srivastava, Prashant K.
    Dong, Yueping
    Takeuchi, Yasuhiro
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2020, 542