| Literature DB >> 34192111 |
Edwin Montes-Orozco1, Roman-Anselmo Mora-Gutierrez2, Sergio-Gerardo De-Los-Cobos-Silva3, Eric-Alfredo Rincon-Garcia3, Gilberto-Sinuhe Torres-Cockrell1, Jorge Juarez-Gomez4, Bibiana Obregon-Quintana5, Pedro Lara-Velazquez3, Miguel-Angel Gutierrez-Andrade3.
Abstract
In this work, we present a methodology to identify COVID-19 spreaders using the analysis of the relationship between socio-cultural and economic characteristics with the number of infections and deaths caused by the COVID-19 virus in different countries. For this, we analyze the information of each country using the complex networks approach, specifically by analyzing the spreaders countries based on the separator set in 5-layer multiplex networks. The results show that, we obtain a classification of the countries based on their numerical values in socioeconomics, population, Gross Domestic Product (GDP), health and air connections; where, in the spreader set there are those countries that have high, medium or low values in the different characteristics; however, the aspect that all the countries belonging to the separator set share is a high value in air connections. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.Entities:
Keywords: COVID-19; Complex networks; complex systems; multiplex networks; optimization; social networks
Year: 2020 PMID: 34192111 PMCID: PMC8043565 DOI: 10.1109/ACCESS.2020.3007726
Source DB: PubMed Journal: IEEE Access ISSN: 2169-3536 Impact factor: 3.367