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Understanding the uneven spread of COVID-19 in the context of the global interconnected economy

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  • Dimitrios Tsiotas
  • Vassilis Tselios

Abstract

Using network analysis, this paper develops a multidimensional methodological framework for understanding the uneven (cross-country) spread of COVID-19 in the context of the global interconnected economy. The globally interconnected system of tourism mobility is modeled as a complex network, where two main stages in the temporal spread of COVID-19 are revealed and defined by the cutting-point of the 44th day from Wuhan. The first stage describes the outbreak in Asia and North America, the second one in Europe, South America, and Africa, while the outbreak in Oceania is spread along both stages. The analysis shows that highly connected nodes in the global tourism network (GTN) are infected early by the pandemic, while nodes of lower connectivity are late infected. Moreover, countries with the same network centrality as China were early infected on average by COVID-19. The paper also finds that network interconnectedness, economic openness, and transport integration are key determinants in the early global spread of the pandemic, and it reveals that the spatio-temporal patterns of the worldwide spread of COVID-19 are more a matter of network interconnectivity than of spatial proximity.

Suggested Citation

  • Dimitrios Tsiotas & Vassilis Tselios, 2021. "Understanding the uneven spread of COVID-19 in the context of the global interconnected economy," Papers 2101.11036, arXiv.org.
  • Handle: RePEc:arx:papers:2101.11036
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    File URL: http://arxiv.org/pdf/2101.11036
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    1. repec:cup:cbooks:9780511771576 is not listed on IDEAS
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    3. Giovanni Bonaccorsi & Francesco Pierri & Matteo Cinelli & Andrea Flori & Alessandro Galeazzi & Francesco Porcelli & Ana Lucia Schmidt & Carlo Michele Valensise & Antonio Scala & Walter Quattrociocchi , 2020. "Economic and social consequences of human mobility restrictions under COVID-19," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(27), pages 15530-15535, July.
    4. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331.
    5. T Gonzalez & M A de la Rubia & K P Hincz & M Comas-Lopez & Laia Subirats & Santi Fort & G M Sacha, 2020. "Influence of COVID-19 confinement on students’ performance in higher education," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-23, October.
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    Cited by:

    1. Dimitrios Tsiotas & Thomas Krabokoukis & Serafeim Polyzos, 2021. "Detecting Tourism Typologies of Regional Destinations Based on Their Spatio-Temporal and Socioeconomic Performance: A Correlation-Based Complex Network Approach for the Case of Greece," Tourism and Hospitality, MDPI, vol. 2(1), pages 1-27, February.

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