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

Zhangbo Yang; Jingen Song; Shanxing Gao; Hui Wang; Yingfei Du; Qiuyue Lin

doi:10.1371/journal.pone.0261335

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

PLoS One. 2021 Dec 14;16(12):e0261335. doi: 10.1371/journal.pone.0261335. eCollection 2021.

Authors

Zhangbo Yang^{1

2}, Jingen Song¹, Shanxing Gao³, Hui Wang³, Yingfei Du⁴, Qiuyue Lin¹

Affiliations

¹ School of Humanities and Social Science, Xi'an Jiaotong University, Xi'an, China.
² Institute for Empirical Social Science Research, Xi'an Jiaotong University, Xi'an, China.
³ School of Management, Xi'an Jiaotong University, Xi'an, China.
⁴ Zhou Enlai School of Government, Nankai University, Xi'an, China.

Abstract

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.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adolescent
Adult
Aged
Algorithms
COVID-19 / transmission*
Child
Child, Preschool
China / epidemiology
Contact Tracing / methods*
Female
Humans
Infant
Male
Middle Aged
Social Network Analysis
Tourism
Young Adult

Grants and funding

This research was supported by National Natural Science Foundation of China (Grant No. 71902155) and National Philosophy and Social Sciences Foundation of China (Grant No. 20VYJ052). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.