National probabilities of the coronavirus spreading over time in Europe based on migration networks

Abstract

Global migration trends (Hatton−Williamson
\n2005, Bálint et al 2017, Farkas–Dövényi 2018)
\ntoday differ from those in previous centuries in
\nterms of both the number of people migrating
\n(as of 2017, 272 million people live in a country
\nother than their country of origin) as well as the
\ngeographical, economic, and cultural distance
\nbetween sending regions and destination
\ncountries. The interconnection between
\ncountries is constantly growing, relationships are
\nexpanding through migration, and people's
\nmovement is increasing.
\nMigration shows strong territorial concentration
\n(Winders 2014); in 2019, half of the global
\nmigrant population lived in nine countries. In
\ninternational migration, there are centres (large
\nhost countries) and global migration destinations,
\nwhich attract migrants over long distances. Such
\nhubs include the USA, Canada, Australia, the
\nUK, Germany, France and Spain.
\nClose migration relationships mean strong
\nexposure and vulnerability to the spread of
\ninfectious diseases. The calculation does not
\nassume that infection can only be caused by
\nmigration, but states that migration relationships
\nbetween countries, that is, their network, well
\nrepresent the spread of infections between
\ncountries.

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