scholarly journals Virus-Information Coevolution Spreading Dynamics on Multiplex Networks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jian Wang ◽  
Xiaolin Qin ◽  
Hongying Fang
Keyword(s):  
Field Theory ◽  
Mathematical Model ◽  
Numerical Simulations ◽  
Systematic Study ◽  
Dynamic Process ◽  
Mean Field Theory ◽  
Mean Field ◽  
Multiplex Networks ◽  
Spreading Dynamics ◽  
Information Spreading

Virus and information spreading dynamics widely exist in complex systems. However, systematic study still lacks for the interacting spreading dynamics between the two types of dynamics. This paper proposes a mathematical model on multiplex networks, which considers the heterogeneous susceptibility and infectivity in two subnetworks. By using a heterogeneous mean-field theory, we studied the dynamic process and outbreak threshold of the system. Through extensive numerical simulations on artificial networks, we find that the virus’s spreading dynamics can be suppressed by increasing the information spreading probability, decreasing the protection power, or decreasing the susceptibility and infectivity.

scholarly journals Competing Complex Information Spreading in Multiplex Social Network

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiang Li ◽  
Bocheng Hou
Keyword(s):  
Field Theory ◽  
Mathematical Model ◽  
Network Science ◽  
Mean Field Theory ◽  
Mean Field ◽  
Global Information ◽  
Multiplex Networks ◽  
Complex Information ◽  
Spreading Dynamics ◽  
Information Spreading

Coevolution spreading dynamics on complex networks is a hot topic, which attracts much attention in network science. This paper proposes a mathematical model to describe the two competing complex information spreading dynamics on multiplex networks. An individual can only accept one of the two pieces of information. A heterogeneous mean-field theory is developed to describe the spreading dynamics. We reveal different regions through Monte Carlo simulations of the competing complex information spreading dynamics: no global information, one information dominant, and two information coexistence. We finally find that the heterogeneity of the multiplex networks’ degree distributions does not qualitatively affect the results.

scholarly journals Ligand rebinding: self-consistent mean-field theory and numerical simulations applied to surface plasmon resonance studies

2005 ◽  
Vol 34 (7) ◽  
pp. 943-958 ◽  
Author(s):  
Manoj Gopalakrishnan ◽  
Kimberly Forsten-Williams ◽  
Theresa R. Cassino ◽  
Luz Padro ◽  
Thomas E. Ryan ◽  
...  
Keyword(s):  
Field Theory ◽  
Surface Plasmon Resonance ◽  
Numerical Simulations ◽  
Surface Plasmon ◽  
Plasmon Resonance ◽  
Mean Field Theory ◽  
Mean Field ◽  
Self Consistent ◽  
Ligand Rebinding

Spreading of Epidemics on Scale-Free Networks with Time Delay

2012 ◽  
Vol 562-564 ◽  
pp. 1386-1389
Author(s):  
Yuan Mei Wang ◽  
Tao Li
Keyword(s):  
Field Theory ◽  
Time Delay ◽  
Mean Field Theory ◽  
Mean Field ◽  
Sir Model ◽  
Scale Free ◽  
Spreading Dynamics ◽  
Scale Free Networks ◽  
The Mean ◽  
Theoretical Results

In the SIR model once a node is cured after infection it becomes permanently immune,but we assume this immunity to be temporary. So we obtain an epidemic model with time delay on scale-free networks. Using the mean field theory the spreading threshold and the spreading dynamics is analyzed. Theoretical results indicate that the threshold is significantly dependent on the topology of scale-free networks and time delay. Numerical simulations confirmed the theoretical results.

scholarly journals A minimal model for household effects in epidemics

2020 ◽  
Author(s):  
Greg Huber ◽  
Mason Kamb ◽  
Kyle Kawagoe ◽  
Lucy Li ◽  
Boris Veytsman ◽  
...  
Keyword(s):  
Field Theory ◽  
Numerical Simulations ◽  
Minimal Model ◽  
Reproduction Number ◽  
Mean Field Theory ◽  
Mean Field ◽  
Household Size ◽  
Transmission Dynamics ◽  
Square Root ◽  
Close Contacts

Shelter-in-place and other confinement strategies implemented in the current COVID-19 pandemic have created stratified patterns of contacts between people: close contacts within households and more distant contacts between the households. The epidemic transmission dynamics is significantly modified as a consequence. We introduce a minimal model that incorporates these household effects in the framework of mean-field theory and numerical simulations. We show that the reproduction number R0 depends on the household size in a surprising way: linearly for relatively small households, and as a square root of size for larger households. We discuss the implications of the findings for the lockdown, test, tracing, and isolation policies.

scholarly journals Containing Epidemic Spreading on Networks with Neighbor Resource Supporting

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Chengcheng Song ◽  
Yanyan Chen ◽  
Ning Chen ◽  
Zhuo Liu ◽  
Xuzhen Zhu ◽  
...  
Keyword(s):  
Field Theory ◽  
Complex Networks ◽  
Numerical Simulations ◽  
Mean Field Theory ◽  
Mean Field ◽  
Limited Resources ◽  
Epidemic Outbreak ◽  
Epidemic Spreading ◽  
Spreading Model ◽  
Outbreak Size

Previous studies revealed that the susceptibility, contacting preference, and recovery probability markedly alter the epidemic outbreak size and threshold. The recovery probability of an infected node is closely related to its obtained resources. How to allocate limited resources to infected neighbors is extremely important for containing the epidemic spreading on complex networks. In this paper, we proposed an epidemic spreading model on complex networks, in which we assume that the node has heterogeneous susceptibility and contacting preference, and susceptible nodes are willing to share their resources to neighbors. Through a developed heterogeneous mean-field theory and a large number of numerical simulations, we find that the recovered nodes provide resources uniformly to their infected neighbor nodes, and the epidemic spreading can be suppressed optimally on homogeneous and heterogeneous networks. Besides, altering the susceptibility and contacting preference does not qualitatively change the results. The susceptibility of the node decreases, which makes the outbreak threshold of epidemic spreading increase, and the outbreak size decreases. Our theory agrees well with the numerical simulations.

Sign in / Sign up

Export Citation Format

Share Document