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Coronavirus and Migration

Analysis of Human Mobility and the Spread of Covid-19

Bibliographic Data

ID15537838
AuthorsIbrahim Sirkeci (0000-0002-2334-7424, corresponding author), M Murat Yüceşahin (0000-0001-9038-464X, Ankara University)
Year2020
Volume17
Issue2
Pages379-398
Publication date2020-04-02
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueMIGRATION LETTERS (JOURNAL)
Journal identifiersISSN: 1741-8984 • E-ISSN: 1741-8992
PublisherDewspublication (PUBLISHER)
DOI10.33182/ml.v17i2.935
OpenAlexW3014438290
LanguageEN
Citations received35
References cited6

Reactions, measures as well as discourses dealing with the current pandemic vary significantly across the world. While some countries were completely locked down, as was the case in Italy, some had claimed to have very few or no cases, as was the case in Turkey and Indonesia by March 10th, 2020. Nevertheless, the spread of COVID-19 from China has been clearly linked to those travelling from Wuhan in Hubei province in Central China. Therefore, it is important to understand the travel density/volume of passengers carried as well as routes from Wuhan through connected main regional air travel hubs across China. In this study, we developed a model on migration and travel intensity that can explain outbreak and spread COVID-19 since it appeared at the end of 2019. We show that the presence of migrant stock populations of Chinese origin and the immigrant stock in China are useful indicators in the prediction of the spread of the outbreak worldwide in the event of interaction with several other macro factors. We argue that monitoring immigrant stock data and travel volume data based on human mobility corridors (i.e. origins and destinations), countries could have been better prepared and taken early measures to contain the spread of COVID-19

Biology · China · Coronavirus disease 2019 (COVID-19 · Demographic economics · Destinations · Economic geography · Economics · Geography · Human migration · Immigration · Infectious disease (medical specialty · Outbreak · Pandemic · Population · Socioeconomics · Sociology · Stock (firearms · Tourism · COVID-19 epidemiological studies · COVID-19 Pandemic Impacts · Demography · Zoonotic diseases and public health

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Unique citing works35
Citations per year5,83
Citation span2020 - 2025 (6)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 34

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