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Identification of COVID-19 Spreaders Using Multiplex Networks Approach
Edwin Montes-Orozco1, Roman-Anselmo Mora-Gutierrez2, Sergio-Gerardo De-Los-Cobos-Silva3
1Posgrado en Ciencias y Tecnologías de la InformaciónUniversidad Autónoma Metropolitana IztapalapaMexico City09340Mexico.
IEEE Access : Practical Innovations, Open Solutions
|June 30, 2021
Summary
This study identifies COVID-19 spreaders by analyzing country socio-economic factors and air travel connections. Countries with high air connectivity were consistently identified as key spreaders, regardless of other factors.
Area of Science:
- Epidemiology
- Network Science
- Socioeconomics
Background:
- The COVID-19 pandemic highlighted the need to understand disease transmission dynamics.
- Identifying key spreaders is crucial for effective public health interventions.
Purpose of the Study:
- To develop a methodology for identifying COVID-19 spreaders.
- To analyze the relationship between socio-cultural, economic factors, and COVID-19 spread.
Main Methods:
- Complex networks approach applied to country-level data.
- Analysis of 5-layer multiplex networks to identify spreader sets.
- Evaluation of socioeconomics, population, GDP, health, and air connectivity.
Main Results:
- A classification of countries based on socio-economic and connectivity data was established.
- Spreader countries exhibited varied socio-economic profiles.
- High air connectivity was a common characteristic among all identified spreader countries.
Conclusions:
- Air connectivity is a critical factor in identifying countries that act as COVID-19 spreaders.
- Multiplex network analysis provides insights into global disease transmission patterns.
