Identification of COVID-19 Spreaders Using Multiplex Networks Approach
Edwin Montes-Orozco, Román Anselmo Mora-Gutiérrez, Sergio Gerardo de-los-Cobos-Silva, Eric Alfredo Rincón-García, Gilberto-Sinuhe Torres-Cockrell, Jorge Juárez‐Gómez, Bibiana Obregón-Quintana, Pedro Lara-Velázquez, Miguel Ángel Gutiérrez Andrade
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.