Human Mobility and Coronavirus Disease 2019 (COVID-19): a Negative Binomial Regression Analysis

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.