共 80 条
Spatial dynamics of an epidemic model with nonlocal infection
被引:60
作者:
Guo, Zun-Guang
[1
,2
,3
]
Sun, Gui-Quan
[2
,4
]
Wang, Zhen
[5
,6
]
Jin, Zhen
[4
]
Li, Li
[7
]
Li, Can
[3
]
机构:
[1] North Univ China, Data Sci & Technol, Taiyuan 030051, Shanxi, Peoples R China
[2] North Univ China, Dept Math, Taiyuan 030051, Shanxi, Peoples R China
[3] Taiyuan Inst Technol, Dept Sci, Taiyuan 030008, Shanxi, Peoples R China
[4] Shanxi Univ, Complex Syst Res Ctr, Taiyuan 030006, Shanxi, Peoples R China
[5] Northwestern Polytech Univ, Sch Mech Engn, Xian 710072, Peoples R China
[6] Northwestern Polytech Univ, Ctr Opt IMagery Anal & Learning Optimal, Xian 710072, Peoples R China
[7] Shanxi Univ Taiyuan, Sch Comp & Informat Technol, Taiyuan 030006, Shanxi, Peoples R China
基金:
中国国家自然科学基金;
中国博士后科学基金;
关键词:
Nonlocal delay;
Disease transmission;
Turing pattern;
Multi-scale analysis;
DISPERSAL SIR MODEL;
TRAVELING-WAVES;
NONLINEAR INCIDENCE;
GLOBAL STABILITY;
TRANSMISSION DYNAMICS;
SATURATION INCIDENCE;
PULSE VACCINATION;
PATTERN-FORMATION;
AVIAN INFLUENZA;
DIFFUSION;
D O I:
10.1016/j.amc.2020.125158
中图分类号:
O29 [应用数学];
学科分类号:
070104 ;
摘要:
Nonlocal infection plays an important role in epidemic spread, which can reflect the real rules of infectious disease. To understand its mechanism on disease transmission, we construct an epidemic model with nonlocal delay and logistic growth. The Turing space for the emergence of stationary pattern is determined by series of inequations by mathematical analysis. Moreover, we use the multi-scale analysis to derive the amplitude equation, and obtain rich pattern structures by controlling the variation of the delay parameter. As the increase of delay parameter, the degree of pattern isolation increase as well as the density of the infected population decrease which prohibits the propagation of the disease in space. The results systematically reveal the impact of nonlocal delay on the spread of infectious diseases and provide some new theoretical supports for controlling the spread of infectious diseases. (C) 2020 Elsevier Inc. All rights reserved.
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