scholarly journals Contact network analysis of Covid-19 in tourist areas——Based on 333 confirmed cases in China

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261335
Author(s):  
Zhangbo Yang ◽  
Jingen Song ◽  
Shanxing Gao ◽  
Hui Wang ◽  
Yingfei Du ◽  
...  
Keyword(s):  
Network Analysis ◽  
Network Structure ◽  
Southern China ◽  
Virus Transmission ◽  
Dynamic Contact ◽  
Contact Network ◽  
Degree Centrality ◽  
Imported Cases ◽  
Epidemiological Characteristics ◽  
Human Networks

The spread of infectious diseases is highly related to the structure of human networks. Analyzing the contact network of patients can help clarify the path of virus transmission. Based on confirmed cases of COVID-19 in two major tourist provinces in southern China (Hainan and Yunnan), this study analyzed the epidemiological characteristics and dynamic contact network structure of patients in these two places. Results show that: (1) There are more female patients than males in these two districts and most are imported cases, with an average age of 45 years. Medical measures were given in less than 3 days after symptoms appeared. (2) The whole contact network of the two areas is disconnected. There are a small number of transmission chains in the network. The average values of degree centrality, betweenness centrality, and PageRank index are small. Few patients have a relatively high contact number. There is no superspreader in the network.

scholarly journals Contact network analysis of patients with Novel Coronavirus Pneumonia - Based on 237 cases in Shaanxi Province

2020 ◽  
Author(s):  
Yang Zhangbo
Keyword(s):  
Network Analysis ◽  
Dynamic Contact ◽  
Shaanxi Province ◽  
Contact Network ◽  
Degree Centrality ◽  
Local Infection ◽  
Strong Ties ◽  
Infected People ◽  
Imported Cases ◽  
Novel Coronavirus

Abstract The spread of novel coronavirus is closely related to the structure of human social networks. Based on 237 cases in Shaanxi Province, using epidemiological retrospective statistics, data visualization, and social network analysis methods, this paper summarized characteristics of patients with new coronary pneumonia in Shaanxi Province, and analyzes these patients’ dynamic contact network structure. The study found that there are many clustered infections through strong ties, about one-third cases are caused by relatives' infection. In the early stages of the epidemic, it was mainly imported cases, and in the later stages, it was mainly local infection cases. The infected people were mainly middle-aged men. Symptoms of imported cases occurred on average 3 days after they arrived, and medical measures were taken on average 5 days later. All cases showed symptoms in less than 2 days on average and were then taken to medical treatment. The virus contact network can be divided into multiple disconnected components. The largest component has 12 patients. The average degree centrality in the network is 0.987. The average betweenness degree is 0. The average closeness degree is 0.452. The average PageRank index is 0.0042. The number of contacts of patients is unevenly distributed in the network.

scholarly journals Analysis of dynamic contact network of patients with COVID-19 in Shaanxi Province of China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhangbo Yang
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Dynamic Contact ◽  
Shaanxi Province ◽  
Contact Network ◽  
Degree Centrality ◽  
Local Infection ◽  
Strong Ties ◽  
Infected People ◽  
Imported Cases

AbstractThe spread of COVID-19 is closely related to the structure of human social networks. Based on 237 cases, by using epidemiological retrospective statistics, data visualization, and social network analysis methods, this paper summarized characteristics of patients with COVID-19 in Shaanxi, China, and analyzed these patients’ dynamic contact network structure. The study found that there are many clustered infections through strong ties, about one-third of cases are caused by relatives' infection. In early stages of the epidemic, imported cases were the most, and in the later stages, local infection cases were the most. The infected people were mostly middle-aged men. Symptoms of imported cases occurred on average of 3 days after they arrived, and medical measures were taken 5 days later on average. All cases showed symptoms in less than 2 days on average and were then taken to medical treatment. The contact network can be divided into multiple disconnected components. The largest component has 12 patients. The average degree centrality in the network is 0.987, average betweenness degree is 0, average closeness degree is 0.452, and average PageRank index is 0.0042. The number of contacts of patients is unevenly distributed in the network.

scholarly journals Bayesian Network Structure and Predictability of Autistic Traits

2020 ◽  
pp. 003329412097815
Author(s):  
Giovanni Briganti ◽  
Donald R. Williams ◽  
Joris Mulder ◽  
Paul Linkowski
Keyword(s):  
Sex Differences ◽  
Network Analysis ◽  
Bayesian Network ◽  
Network Structure ◽  
Network Connectivity ◽  
Autistic Traits ◽  
Data Set ◽  
Conditional Dependence ◽  
Bayesian Network Structure ◽  
Male Subjects

The aim of this work is to explore the construct of autistic traits through the lens of network analysis with recently introduced Bayesian methods. A conditional dependence network structure was estimated from a data set composed of 649 university students that completed an autistic traits questionnaire. The connectedness of the network is also explored, as well as sex differences among female and male subjects in regard to network connectivity. The strongest connections in the network are found between items that measure similar autistic traits. Traits related to social skills are the most interconnected items in the network. Sex differences are found between female and male subjects. The Bayesian network analysis offers new insight on the connectivity of autistic traits as well as confirms several findings in the autism literature.

scholarly journals Tight knit under stress: colony resilience to the loss of tandem leaders during relocation in an Indian ant

2015 ◽  
Vol 2 (9) ◽  
pp. 150104 ◽  
Author(s):  
Swetashree Kolay ◽  
Sumana Annagiri
Keyword(s):  
Network Analysis ◽  
Social Insects ◽  
Network Structure ◽  
Similar Rate ◽  
Tandem Running ◽  
Frequent Event ◽  
Random Removal ◽  
Task Organization

The movement of colonies from one nest to another is a frequent event in the lives of many social insects and is important for their survival and propagation. This goal-oriented task is accomplished by means of tandem running in some ant species, such as Diacamma indicum . Tandem leaders are central to this process as they know the location of the new nest and lead colony members to it. Relocations involving targeted removal of leaders were compared with unmanipulated and random member removal relocations. Behavioural observations were integrated with network analysis to examine the differences in the pattern of task organization at the level of individuals and that of the colony. All colonies completed relocation successfully and leaders who substituted the removed tandem leaders conducted the task at a similar rate having redistributed the task in a less skewed manner. In terms of network structure, this resilience was due to significantly higher density and outcloseness indicating increased interaction between substitute leaders. By contrast, leader–follower interactions and random removal networks showed no discernible changes. Similar explorations of other goal-oriented tasks in other societies will possibly unveil new facets in the interplay between individuals that enable the group to respond effectively to stress.

scholarly journals A study on the influence of Korean Middle School students' relationship through Science class applying STAD cooperative learning

2018 ◽  
Vol 8 (4) ◽  
pp. 291 ◽  
Author(s):  
Dongryeul Kim
Keyword(s):  
Middle School ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Middle School Students ◽  
Collaborative Learning ◽  
Closeness Centrality ◽  
Degree Centrality ◽  
Science Class ◽  
School Students

  In order to find out the influence of Korean Middle School Students' relationship by science class applying STAD collaborative learning, this study conducted a social network analysis and sought to analyze the communication networks within the group and identified the change process of the type. The subject of this study was 30 students of the second grade at the girls' middle school located in Korea's Metropolitan City. For five weeks, science class applying STAD Collaborative Learning was implemented in the ‘reproduction and generation’ chapter. First, the class social network analysis showed that all the prices of density, degree centrality, closeness centrality, and betweenness centrality have risen after science class applying STAD Collaborative Learning. Also, the classroom's relationship index has improved. In other words, STAD Collaborative Learning encouraged interaction among students. Second, in order to research popularity, students' centrality analysis through the class social network analysis showed that top-ranked students' values of density, degree centrality, closeness centrality, and betweenness centrality appeared commonly high after science class applying STAD Collaborative Learning. Third, the analysis of the communication network change within six groups showed that all channel type appeared most often and circle type also appeared anew after science class applying STAD Collaborative Learning. In other words, it was possible to exchange information freely and communicate with all members of the group through STAD Collaborative Learning.

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