ABSTRACT
Mobility functional areas are tools based on human mobility that can be useful for spatial and transport planning in delicate situations such as the COVID-19 pandemic. In this work, we aim to map functional areas in Spain from four days corresponding to different phases of the disease. For that goal, mobile phone data provided by Spanish Statistical National Institute (INE) has been used due to its value and potential to provide constantly updated information of mobility at almost-real time. The methodology consists of a network analysis over an origin-destination matrix to obtain modularity values for 3214 population cells provided by the INE. These values were then used to cluster the cells into functional areas. The results show how different confinement and mobility restriction policies influence the amount, size and shape of the functional areas, and therefore, they affect access to services or jobs.
ABSTRACT
This work seeks to show Twitter as an alternative data source for the study of the pandemic caused by the COVID-19 virus in Spain. For this work, an analysis of the spatial and temporal distribution of the sample of users obtained in three different periods of the year 2020 is proposed, and then the obtained results are compared with the same periods of the year prior to the pandemic. A space-time analysis of the use of terms associated with the disease is also elaborated, and heat maps are made to observe the impact caused in the activity of two cities of relevant tourist weight. The obtained results indicate a sharp decrease in the number of users who publish geolocated tweets in the country throughout 2020, especially in the second half of the year and in the interior provinces of the peninsula. A less pronounced decrease in the number of users is also observed in coastal areas and provinces oriented to the tourism sector.