Pattern Dynamics of Nonlocal Delay SI Epidemic Model with the Growth of the Susceptible following Logistic Mode

In this paper, we investigate pattern dynamics of a nonlocal delay SI epidemic model with the growth of susceptible population following logistic mode. Applying the linear stability theory, the condition that the model generates Turing instability at the endemic steady state is analyzed; then, the e...

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Main Authors: Zun-Guang Guo, Jing Li, Can Li, Juan Liang, Yiwei Yan
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/9217387
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author Zun-Guang Guo
Jing Li
Can Li
Juan Liang
Yiwei Yan
author_facet Zun-Guang Guo
Jing Li
Can Li
Juan Liang
Yiwei Yan
author_sort Zun-Guang Guo
collection DOAJ
description In this paper, we investigate pattern dynamics of a nonlocal delay SI epidemic model with the growth of susceptible population following logistic mode. Applying the linear stability theory, the condition that the model generates Turing instability at the endemic steady state is analyzed; then, the exact Turing domain is found in the parameter space. Additionally, numerical results show that the time delay has key effect on the spatial distribution of the infected, that is, time delay induces the system to generate stripe patterns with different spatial structures and affects the average density of the infected. The numerical simulation is consistent with the theoretical results, which provides a reference for disease prevention and control.
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institution Kabale University
issn 1076-2787
1099-0526
language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-c63981c810094b59b60c01af6acac57b2025-02-03T01:04:28ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/92173879217387Pattern Dynamics of Nonlocal Delay SI Epidemic Model with the Growth of the Susceptible following Logistic ModeZun-Guang Guo0Jing Li1Can Li2Juan Liang3Yiwei Yan4Department of Science, Taiyuan Institute of Technology, Taiyuan, Shanxi 030008, ChinaCollege of Applied Mathematics, Shanxi University of Finance and Economics, Taiyuan, Shanxi 030006, ChinaDepartment of Science, Taiyuan Institute of Technology, Taiyuan, Shanxi 030008, ChinaDepartment of Science, Taiyuan Institute of Technology, Taiyuan, Shanxi 030008, ChinaDepartment of Science, Taiyuan Institute of Technology, Taiyuan, Shanxi 030008, ChinaIn this paper, we investigate pattern dynamics of a nonlocal delay SI epidemic model with the growth of susceptible population following logistic mode. Applying the linear stability theory, the condition that the model generates Turing instability at the endemic steady state is analyzed; then, the exact Turing domain is found in the parameter space. Additionally, numerical results show that the time delay has key effect on the spatial distribution of the infected, that is, time delay induces the system to generate stripe patterns with different spatial structures and affects the average density of the infected. The numerical simulation is consistent with the theoretical results, which provides a reference for disease prevention and control.http://dx.doi.org/10.1155/2020/9217387
spellingShingle Zun-Guang Guo
Jing Li
Can Li
Juan Liang
Yiwei Yan
Pattern Dynamics of Nonlocal Delay SI Epidemic Model with the Growth of the Susceptible following Logistic Mode
Complexity
title Pattern Dynamics of Nonlocal Delay SI Epidemic Model with the Growth of the Susceptible following Logistic Mode
title_full Pattern Dynamics of Nonlocal Delay SI Epidemic Model with the Growth of the Susceptible following Logistic Mode
title_fullStr Pattern Dynamics of Nonlocal Delay SI Epidemic Model with the Growth of the Susceptible following Logistic Mode
title_full_unstemmed Pattern Dynamics of Nonlocal Delay SI Epidemic Model with the Growth of the Susceptible following Logistic Mode
title_short Pattern Dynamics of Nonlocal Delay SI Epidemic Model with the Growth of the Susceptible following Logistic Mode
title_sort pattern dynamics of nonlocal delay si epidemic model with the growth of the susceptible following logistic mode
url http://dx.doi.org/10.1155/2020/9217387
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