ABSTRACT
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.
Subject(s)
COVID-19 , Epidemics , China/epidemiology , Disease Outbreaks , Humans , SARS-CoV-2 , Social StructureABSTRACT
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.
Subject(s)
COVID-19/transmission , Contact Tracing/methods , Adolescent , Adult , Aged , Algorithms , Child , Child, Preschool , China/epidemiology , Female , Humans , Infant , Male , Middle Aged , Social Network Analysis , Tourism , Young AdultABSTRACT
The 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.
Subject(s)
COVID-19 , Contact Tracing , SARS-CoV-2 , Social Networking , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/transmission , Child , Child, Preschool , China/epidemiology , Female , Humans , Male , Middle Aged , Retrospective StudiesABSTRACT
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.