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Public Health . Human mobility and coronavirus disease 2019 (COVID-19): a negative binomial regression analysis

tetano

Editor, Senior Moderator
Public Health


. 2020 Jul 10;185:364-367.
doi: 10.1016/j.puhe.2020.07.002. Online ahead of print.
Human mobility and coronavirus disease 2019 (COVID-19): a negative binomial regression analysis


L I Oztig[SUP] 1 [/SUP], O E Askin[SUP] 2 [/SUP]



Affiliations
Free PMC article

Abstract

Objectives: This study aimed to examine the link between human mobility and the number of coronavirus disease 2019 (COVID-19)-infected people in countries.
Study design: Our data set covers 144 countries for which complete data are available. To analyze the link between human mobility and COVID-19-infected people, our study focused on the volume of air travel, the number of airports, and the Schengen system.
Methods: To analyze the variation in COVID-19-infected people in countries, we used negative binomial regression analysis.
Results: Our findings suggest a positive relationship between higher volume of airline passenger traffic carried in a country and higher numbers of patients with COVID-19. We further found that countries which have a higher number of airports are associated with higher number of COVID-19 cases. Schengen countries, countries which have higher population density, and higher percentage of elderly population are also found to be more likely to have more COVID-19 cases than other countries.
Conclusions: The article brings a novel insight into the COVID-19 pandemic from a human mobility perspective. Future research should assess the impacts of the scale of sea/bus/car travel on the epidemic. The findings of this article are relevant for public health authorities, community and health service providers, as well as policy-makers.

Keywords: Airports; COVID-19; Human mobility; Schengen countries.
 
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