scholarly journals Exploring the Epidemic Spreading in a Multilayer Metapopulation Network by considering Individuals’ Periodic Travelling

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Dun Han ◽  
Qi Shao ◽  
Dandan Li
Keyword(s):  
Diffusion Model ◽  
Mean Field ◽  
Field Method ◽  
Epidemic Spreading ◽  
Epidemic Threshold ◽  
Mobility Rate ◽  
Frobenius Theorem ◽  
Fluctuation Range ◽  
The Mean ◽  
New Perspective

The convenience of transportation brings the diversity of individuals’ travelling modes; in this paper, we present an improved epidemic diffusion model in a multilayer metapopulation network. Firstly, we construct the metapopulation network with different travelling ways, and then, the epidemic spreading threshold is calculated by means of the mean-field method. Taking the periodicity of individuals’ travelling into account, we further explore the epidemic diffusion model with individuals’ periodic travelling and deduce the epidemic spreading threshold using the Perron–Frobenius theorem. Our results show that if all individuals in each area decide to move, the epidemic threshold can be effectively raised while each individual chooses an unbiased region to arrive. In addition, with the increase of individuals’ mobility rate or regional heterogeneous infection coefficient, the fluctuation range of the density of infected becomes larger, while the fluctuation period is almost unchanged. However, the change of individuals’ periodic motion could cause the change of the fluctuation period of infected density. We try to provide a new perspective for the research of metapopulation.

The analysis of epidemic spreading on clique-overlapping growth network

2020 ◽  
Vol 34 (26) ◽  
pp. 2050235
Author(s):  
Zhenzhou Lin
Keyword(s):  
Theoretical Analysis ◽  
Mean Field Theory ◽  
Mean Field ◽  
Epidemic Outbreak ◽  
Epidemic Spreading ◽  
Epidemic Threshold ◽  
Epidemic Dynamics ◽  
Immunization Strategies ◽  
The Mean ◽  
Real Complex

In this paper, we propose a new clique-overlapping growth network and study the epidemic spreading on it. We verify by simulation and theoretical analysis that the degree distribution follows a power-law form. Then, we have simulated the epidemic dynamics in this clique-overlapping growth network. Based on the mean-field theory, we have obtained the theoretical epidemic threshold. We find that the epidemic threshold is related to the evolution mechanism of the network model. The theoretical analysis is well consistent with the simulation results. The results in this model can help people understand the epidemic spreading of various processes, such as infectious diseases, computer viruses, gossips, and so on in real complex networks. Moreover, the appropriate immunization strategies can also be designed based on our results, to hold back the trend of epidemic outbreak.

The Applicability of the Mean Field Method in the Optical Bistability

1986 ◽  
pp. 173-177
Author(s):  
I. M. Popescu ◽  
E. N. Stefanescu ◽  
P. E. Sterian
Keyword(s):  
Optical Bistability ◽  
Mean Field ◽  
Field Method ◽  
The Mean

Superconducting and other phases in organic high polymers of polyacenic carbon skeletons. II. The mean field method

1986 ◽  
Vol 85 (5) ◽  
pp. 3097-3102 ◽  
Author(s):  
M. Kimura ◽  
H. Kawabe ◽  
K. Nishikawa ◽  
S. Aono
Keyword(s):  
Mean Field ◽  
Field Method ◽  
The Mean ◽  
High Polymers

GENERALIZATION OF THE MEAN-FIELD METHOD FOR POWER-LAW DISTRIBUTIONS

2006 ◽  
Vol 16 (01) ◽  
pp. 129-135 ◽  
Author(s):  
TARO TOYOIZUMI ◽  
KAZUYUKI AIHARA
Keyword(s):  
Computational Complexity ◽  
Financial Markets ◽  
Mean Field ◽  
Field Method ◽  
World Systems ◽  
Developed Turbulence ◽  
Binary State ◽  
The Mean ◽  
Generalized Mean ◽  
Power Law Distributions

Recently much attention has been paid to the nonextensive canonical distributions: the α-families. Such distributions have been found in many real-world systems such as fully developed turbulence and financial markets. In this paper, a generalized mean-field method to approximate the expectations of the α-families is proposed. We calculate the α′-projection of a probability distribution to find that the computational complexity to approximate the expectations is greatly reduced with a proper choice of the projection-index α′. We apply this method to a simple binary-state system and compare the results with direct numerical calculations.

Research on SIQRS Spreading Dynamic Model with Feedback Mechanism on Scale-Free Networks

2014 ◽  
Vol 989-994 ◽  
pp. 4524-4527
Author(s):  
Tao Li ◽  
Yuan Mei Wang ◽  
You Ping Yang
Keyword(s):  
Dynamic Model ◽  
Mean Field Theory ◽  
Mean Field ◽  
Feedback Mechanism ◽  
Epidemic Spreading ◽  
Scale Free ◽  
Spreading Dynamics ◽  
Scale Free Networks ◽  
The Mean ◽  
The Relationship

A modified spreading dynamic model with feedback-mechanism based on scale-free networks is presented in this study. Using the mean field theory, the spreading dynamics of the model is analyzed. The spreading threshold and equilibriums are derived. The relationship between the spreading threshold, the epidemic steady-state and the feedback-mechanism is analyzed in detail. Theoretical results indicate the feedback-mechanism can increase the spreading threshold, resulting in effectively controlling the epidemic spreading.

Modeling and Modifying the Foraging Strategy in Swarm Robots

2011 ◽  
Vol 467-469 ◽  
pp. 269-274 ◽  
Author(s):  
Dong Xu ◽  
Bai Long Liu ◽  
Ru Bo Zhang
Keyword(s):  
Swarm Intelligence ◽  
Cooperative Behavior ◽  
Mean Field ◽  
Foraging Strategy ◽  
Field Method ◽  
Ant System ◽  
Modified Method ◽  
Swarm Robots ◽  
The Mean ◽  
Foraging Task

Swarm Intelligence which emerges from interactions of simple individuals can be used to solve many problems. The foraging task in ant system is often considered as the prototype of cooperative behavior in Swarm Intelligence. The foraging model in swarm robots which considers the random feature of individual robot is built using the mean field method. Then the conflict between robots which influences the performance is observed. To solve this problem, a modified foraging strategy based on pheromone is proposed. From the simulations in Starlogo platform, it is shown that the modified method can reduces the conflict of robots and increase the performance of the system.

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