ArticleIEEE access : practical innovations, open solutions2020
Identification of COVID-19 Spreaders Using Multiplex Networks Approach.
Article in IEEE access : practical innovations, open solutions, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Modeling roles and trade-offs in multiplex networks.Nature communications · 2026Article
- Understanding the uneven spread of COVID-19 in the context of the global interconnected economy.Scientific reports · 2022Article
- Computational and Mathematical Methods in Medicine Prediction of COVID-19 in BRICS Countries: An Integrated Deep Learning Model of CEEMDAN-R-ILSTM-Elman.Computational and mathematical methods in medicine · 2022Article
- CNN supported automated recognition of Covid-19 infection in chest X-ray images.Materials today. Proceedings · 2022Article
- Leveraging artificial intelligence to analyze the COVID-19 distribution pattern based on socio-economic determinants.Sustainable cities and society · 2021Article
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Authors and funding
9 authors.
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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.
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