scholarly journals Effect of time delay on pattern dynamics in a spatial epidemic model

2014 ◽  
Vol 412 ◽  
pp. 137-148 ◽  
Author(s):  
Yi Wang ◽  
Jinde Cao ◽  
Gui-Quan Sun ◽  
Jing Li
2017 ◽  
Vol 292 ◽  
pp. 390-399 ◽  
Author(s):  
Li-Peng Song ◽  
Rong-Ping Zhang ◽  
Li-Ping Feng ◽  
Qiong Shi

PLoS ONE ◽  
2016 ◽  
Vol 11 (12) ◽  
pp. e0168127 ◽  
Author(s):  
Chiyori T. Urabe ◽  
Gouhei Tanaka ◽  
Kazuyuki Aihara ◽  
Masayasu Mimura

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Zun-Guang Guo ◽  
Jing Li ◽  
Can Li ◽  
Juan Liang ◽  
Yiwei Yan

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.


1997 ◽  
Vol 34 (3) ◽  
pp. 698-710 ◽  
Author(s):  
Håkan Andersson ◽  
Boualem Djehiche

We study the long-term behaviour of a sequence of multitype general stochastic epidemics, converging in probability to a deterministic spatial epidemic model, proposed by D. G. Kendall. More precisely, we use branching and deterministic approximations in order to study the asymptotic behaviour of the total size of the epidemics as the number of types and the number of individuals of each type both grow to infinity.


2009 ◽  
Vol 19 (4) ◽  
pp. 1656-1685 ◽  
Author(s):  
Rick Durrett ◽  
Daniel Remenik

1997 ◽  
Vol 34 (03) ◽  
pp. 698-710
Author(s):  
Håkan Andersson ◽  
Boualem Djehiche

We study the long-term behaviour of a sequence of multitype general stochastic epidemics, converging in probability to a deterministic spatial epidemic model, proposed by D. G. Kendall. More precisely, we use branching and deterministic approximations in order to study the asymptotic behaviour of the total size of the epidemics as the number of types and the number of individuals of each type both grow to infinity.


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