scholarly journals Complex Contact Network of Patients at the Beginning of an Epidemic Outbreak: An Analysis Based on 1218 COVID-19 Cases in China

Author(s):  
Zhangbo Yang ◽  
Jiahao Zhang ◽  
Shanxing Gao ◽  
Hui Wang

The spread of viruses essentially occurs through the interaction and contact between people, which is closely related to the network of interpersonal relationships. Based on the epidemiological investigations of 1218 COVID-19 cases in eight areas of China, we use text analysis, social network analysis and visualization methods to construct a dynamic contact network of the epidemic. We analyze the corresponding demographic characteristics, network indicators, and structural characteristics of this network. We found that more than 65% of cases are likely to be infected by a strong relationship, and nearly 40% of cases have family members infected at the same time. The overall connectivity of the contact network is low, but there are still some clustered infections. In terms of the degree distribution, most cases’ degrees are concentrated between 0 and 2, which is relatively low, and only a few ones have a higher degree value. The degree distribution also conforms to the power law distribution, indicating the network is a scale-free network. There are 17 cases with a degree greater than 10, and these cluster infections are usually caused by local transmission. The first implication of this research is we find that the COVID-19 spread is closely related to social structures by applying computational sociological methods for infectious disease studies; the second implication is to confirm that text analysis can quickly visualize the spread trajectory at the beginning of an epidemic.

2013 ◽  
Vol 753-755 ◽  
pp. 2959-2962
Author(s):  
Jun Tao Yang ◽  
Hui Wen Deng

Assigning the value of interest to each node in the network, we give a scale-free network model. The value of interest is related to the fitness and the degree of the node. Experimental results show that the interest model not only has the characteristics of the BA scale-free model but also has the characteristics of fitness model, and the network has a power-law distribution property.


2006 ◽  
Vol 43 (3) ◽  
pp. 665-677 ◽  
Author(s):  
J. E. Yukich

We consider a family of long-range percolation models (Gp)p>0on ℤdthat allow dependence between edges and have the following connectivity properties forp∈ (1/d, ∞): (i) the degree distribution of vertices inGphas a power-law distribution; (ii) the graph distance between pointsxandyis bounded by a multiple of logpdlogpd|x-y| with probability 1 -o(1); and (iii) an adversary can delete a relatively small number of nodes fromGp(ℤd∩ [0,n]d), resulting in two large, disconnected subgraphs.


2010 ◽  
Vol 44-47 ◽  
pp. 849-853
Author(s):  
Jun Li ◽  
Yan Niu

A model of detecting an abnormal IP traffic in a subset of network is described. The model is based on the hypothesis that random sampling subnet are the same probability distribution as the entire network if some conditions are met with, nodes’s degree in IP traffic can be processed as a power-law distribution in scale-free network . The model analyzes the power exponent and relations between the anomalous behavior and parameter r. Finally, a test was conducted by the data, some type attacks could be identified exactly. the model provides a new framework for intrusion-detection system.


Author(s):  
Y. Zeng

Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network’s power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network’s degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network’s main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc.) for networking a standard and base datum.


2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Weiwei Cao ◽  
Xiangnan Feng ◽  
Jianmin Jia ◽  
Hong Zhang

Understanding the structure of the Chinese railway network (CRN) is crucial for maintaining its efficiency and planning its future development. To advance our knowledge of CRN, we modeled CRN as a complex weighted network and explored the structural characteristics of the network via statistical evaluations and spatial analysis. Our results show CRN as a small-world network whose train flow obeys power-law decaying, demonstrating that CRN is a mature transportation infrastructure with a scale-free structure. CRN also shows significant spatial heterogeneity and hierarchy in its regionally uneven train flow distribution. We then examined the nodal centralities of CRN using four topological measures: degree, strength, betweenness, and closeness. Nodal degree is positively correlated with strength, betweenness, and closeness. Unlike the common feature of a scale-free network, the most connected nodes in CRN are not necessarily the most central due to underlying geographical, political, and socioeconomic factors. We proposed an integrated measure based on the four centrality measures to identify the global role of each node and the multilayer structure of CRN and confirm that stable connections hold between different layers of CRN.


2006 ◽  
Vol 20 (14) ◽  
pp. 815-820 ◽  
Author(s):  
JIAN-GUO LIU ◽  
ZHONG-TUO WANG ◽  
YAN-ZHONG DANG

It has been found that the networks with scale-free degree distribution are very resilient for random failures. The purpose of this work is to determine the network design guidelines which maximize the network robustness for random failures when the average number of links per node of the network is constant. The optimal value of the degree distribution exponent and the minimum connectivity to different network sizes are given in this paper. Finally, the optimization strategy on how to improve the evolving network robustness is given.


2006 ◽  
Vol 43 (03) ◽  
pp. 665-677
Author(s):  
J. E. Yukich

We consider a family of long-range percolation models (G p ) p>0 on ℤ d that allow dependence between edges and have the following connectivity properties for p ∈ (1/d, ∞): (i) the degree distribution of vertices in G p has a power-law distribution; (ii) the graph distance between points x and y is bounded by a multiple of log pd log pd | x - y | with probability 1 - o(1); and (iii) an adversary can delete a relatively small number of nodes from G p (ℤ d ∩ [0, n] d ), resulting in two large, disconnected subgraphs.


2011 ◽  
Vol 5 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Steve Kirkland ◽  
Debdas Paul

For a connected graph G, we derive tight inequalities relating the smallest signless Laplacian eigenvalue to the largest normalized Laplacian eigenvalue. We investigate how vectors yielding small values of the Rayleigh quotient for the signless Laplacian matrix can be used to identify bipartite subgraphs. Our results are applied to some graphs with degree sequences approximately following a power law distribution with exponent value 2:1 (scale-free networks), and to a scale-free network arising from protein-protein interaction.


2012 ◽  
Vol 22 (04) ◽  
pp. 1250094 ◽  
Author(s):  
YULI ZHAO ◽  
FRANCIS C. M. LAU ◽  
ZHILIANG ZHU ◽  
HAI YU

This paper reports the characteristics and performance of a new type of Luby Transform codes, namely scale-free Luby Transform (SF-LT) codes. In the SF-LT codes, the degree of the encoded symbol follows a modified power-law distribution. Moreover, the complexity and decoding performance of SF-LT codes are compared with LT codes based on robust soliton degree distribution and LT codes based on suboptimal degree distribution. The results show that SF-LT codes outperform other LT codes in terms of the probability of successful decoding over an ideal channel and a binary erasure channel. Moreover, the encoding/decoding complexity for the SF-LT codes is superior.


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