Epidemics on a weighted network with tunable degree–degree correlation

Lopes, Fabio

doi:10.1016/j.mbs.2014.03.013

Cited by 3 publications

(3 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Piraveenan et al [27], through the study of the correlation between the out-degree of the source node and the out-degree of the target node in the directed biological network, as well as the correlation between the indegree of the source node and the in-degree of the target node, explored the assortativity of the network, concluding that the biological network showed a positive correlation. Lopes, F. M [28] revealed the influence of degree-degree correlation on the epidemic network, finding that the epidemic network presented assortative mixing patterns. When the degree-degree correlation coefficient increased (decreased), the basic reproduction number of the epidemic would increase (decrease).…”

Section: ) Relevant Research On the Assortativity Characteristics Of Other Networkmentioning

confidence: 98%

Assortative Analysis of Bulk Trade Complex Network on Maritime Silk Road

et al. 2020

View full text Add to dashboard Cite

Assortativity, one of the mixing patterns of complex networks, is characterized by measuring whether the nodes are preferentially connected to the nodes with a similar scale. While numerous studies have examined the assortative characteristics of various real-world networks, few studies have attempted to analyze the assortativity of networks in which the subject of trade is bulk. The novelty of this research is that, for the first time, the assortative coefficient method in physics is introduced into the bulk trade network, and the Automatic Identification System (AIS) data is used to explore the assortative mixing characteristics of the network. From the perspective of multi-scale (port and country) and multidimensional (node, link, and network) structure, this paper reveals the tendency of trade connection and explores the trade rules of bulk in networks. The results show that: (1) The trade network of bulk on the Maritime Silk Road is assortative. With the increase of spatial scale, the extent of assortativity is also gradually increasing; (2) In the bulk network of ports, trade cooperation shows the rule of distance attenuation; In the national bulk network, it shows the rule of preferential connection; (3) Ports with high out-degree will export bulk to the ports with high out-degree with broad market, while countries with high out-degree export to high in-degree countries with strong demand. The present study is expected to provide valuable references for port planning, national formulation of scientific bulk trade strategy, and promotion of coordinated development of bulk trade network along the Maritime Silk Road.

show abstract

Section: ) Relevant Research On the Assortativity Characteristics Of Other Networkmentioning

confidence: 98%

Assortative Analysis of Bulk Trade Complex Network on Maritime Silk Road

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Graph theory and in particular complex networks have been a widely studied area especially in the last decades with increased amount of data. Several works studied various types of interactions on complex networks, such as rumor and gossip propagation [1], [2], ideological opinion spread [3] and finally physical, infectious relations that can spread disease [4], [5], [6], [7], [8], [9], [10]. Some focused on epidemics spread via sexual contacts [9], [10], while others followed a more general approach regardless of the type of the disease [5], [6], [7], [8] .…”

Section: Related Workmentioning

confidence: 99%

“…References [4], [7], [8] investigated weighted networks, where edge weights correspond to the probability for disease to spread from the infected vertex to susceptible vertex in SI/SIR models, where S, I and R stand for susceptible, infected and recovered states, respectively. This is also the approach followed in this work where we represent different types of interactions with different weights which correspond to the probability of infection.…”

Section: Related Workmentioning

confidence: 99%

Multi-layer network approach in modeling epidemics in an urban town

Meliksah¹,

Bingol²

2021

Preprint

View full text Add to dashboard Cite

The last 2 years have been an extraordinary time with Covid-19 pandemic killing millions, affecting and distressing billions of people worldwide. Countries and towns took various measures such as turning school and work to remote and prohibiting social relations via curfews. In order to estimate the impact of these lockdown scenarios, we propose a multi-layer undirected weighted network, where vertices are the individuals of a town that tend to interact locally. In this network, there are seven layers such as "household", "work", "school", and "friends". Edges in a layer represent interactions that can cause a disease to spread. Depending on the type and intensity of the interactions, transmission probabilities are assigned to edges. With this layered-architecture, various lockdown scenarios can be simulated by adding or removing layers. Our simulations indicate that locking down "friends" layer has the highest impact.

show abstract

Adaptive Sis Epidemic Models on Heterogeneous Networks With Demographics and Risk Perception

2018

View full text Add to dashboard Cite

In the context of epidemic spreading on networks, there are at least three concerns that should be considered. Firstly, the demographic process can change the underlying network structure and thus affect the disease spreading; secondly, the attachment probability of newcomers (namely, newborn or immigrated nodes) to other nodes depends on the degrees and states of existing nodes in the network; and thirdly, newcomers may remove some dangerous contacts once they perceive the risk of disease. In view of these facts, we propose two high-dimensional susceptible-infectious-susceptible (SIS) epidemic models on heterogeneous networks with demographics and risk perception — one that neglects both the degree and state correlations among nodes and the other that reserves the state correlation. Then the log-normal moment closure is adopted to reduce the dimensions of models. The basic reproduction numbers of the two corresponding low-dimensional models are derived. It is found that the basic reproduction numbers of the two models are different. In spite of this, both of them show that increasing recruitment will help to inhibit the disease spreading. In addition, numerical results demonstrate that the extent to which newcomers avoid contacting with infectious nodes can affect both the epidemic threshold and the equilibrium prevalence. Finally, comparisons between numerical and stochastic simulations indicate that the model with state correlation is more accurate.

show abstract

Epidemics on a weighted network with tunable degree–degree correlation

Cited by 3 publications

References 16 publications

Assortative Analysis of Bulk Trade Complex Network on Maritime Silk Road

Assortative Analysis of Bulk Trade Complex Network on Maritime Silk Road

Multi-layer network approach in modeling epidemics in an urban town

Adaptive Sis Epidemic Models on Heterogeneous Networks With Demographics and Risk Perception

Contact Info

Product

Resources

About