The Scientific Data journal, belonging to the Nature editorial group, has published the article that presents the COVID-19 Flow-Maps initiative, an open geographic information system on COVID-19 and the mobility of citizens in Spain, which has been developed in the Barcelona Supercomputing Center (BSC).
It is an open geographic information system that integrates cross-referenced geolocated data on human mobility, at different resolution scales, and COVID-19 cases. The article presents the different integrated datasets consolidated in an accessible resource as well as a visualization tool.
Under the title “COVID-19 Flow-Maps an open geographic information system on COVID-19 and human mobility for Spain”, the article shows how the integration of Flow-Maps mobility and incidence data is necessary to estimate the risk of contagion of Covid-19 from a certain area associated with the influx of citizens from other geographical areas.
For example, in a study in progress, datasets from the COVID-19 Flow-Maps platform have been used to analyze the effect of the policy of closing bars and restaurants applied in Catalonia between October and November. The study compares the mobility differences with the evolution of cases observed during five weeks between Barcelona and Madrid, where the restrictions were not applied. Preliminary results indicate that these measures adopted by the Catalan Government had an impact on mobility, which was reduced, especially on weekends. In addition, it caused citizens to change their behavior. That is to say, they do not replace the meeting with friends and family in restaurants, but they remain in their own area.
The results of the study, which is still in the review phase, also point that the reduction in mobility shows a statistically significant correlation with the reduction of cases, which suggests that the policy of closing bars and restaurants introduced by the Catalan Government contributed to slowing down the growth rate of the incidence of COVID-19 in Catalonia.
Currently, the relationship between mobility and evolution of cases continues to be actively investigated with the aim of identifying the non-pharmacological policies and interventions that have had the best impact on the control of the pandemic.