Investigating mobility in the spring of 2020 means having the worldwide crisis triggered by the coronavirus pandemic in front of our eyes. Although mobility had to be rethought even before the present crisis, i.e., in an era that an Italian writer, Stefano Massini (Newspaper “La Repubblica”, April 2020) has called “Precovidic”, it is clear that the current situation has, on the one hand, accelerated the process and, on the other hand, has determined further constraints in the search for another solution. The need for physical distance between individuals is a variable that had never before entered the manuals of transport and urban planning.
The COVID-19 pandemics is forcing citizens to limit their displacements from home to the minimum and reduce their social interactions. Despite these immediate and hopefully temporary changes, COVID-19 is expected to have a long-term impact on society, economics and culture. There is an ongoing discussion in Europe about the possibility to use tracking and geolocation to take measures for preventing new pandemics like the current one to spread. These methods have been widely and fruitfully used in some Asian countries, but are quite frowned upon in Europe due to privacy and individual freedom concerns.
Here, we report how mobility data collected through mobile phone apps can be used in the assessment of the status of the mobility ecosystems while protecting the privacy of citizens.
The starting point of our analysis is High-Precision Location-Based (HFLB) data collected via mobile phones app, monitoring the movements of individuals from early January to the end of March 2020. The HFLB data we are using has been through mobile phone applications by CUEBIQ a leader company in geolocated data. In principle, these data provide information about all the places visited by a set of individuals, independently of the specific transportation mean adopted. At the same time, nothing is known about the person’s identity, neither the name, the gender or the age nor the purpose of his/her movements.
While trying to infer sensitive personal information about individual mobility patterns is (hopefully) illegal in Europe, understanding the scope for a trip can reveal a lot about how collective habits have changed during the COVID-19 the lockdown. To this end, we crossed CUEBIQ data with OpenStreetMap, to enrich the locations visited by the individuals with labels associated with relevant Points of Interests (POIs) found in a given area.
In the end, we were able to know if a person visited the following locations:
Using the Italian Census Areas, we were also able to identify home and the workplace of each individual with some degree of approximation. The intrinsic noise of the position we had allows assigning a location with a precision of around 100m.
We used this information to analyze the behavior of individuals in different regions of Italy. Did they stay home in the end? In the interactive graph below, it is possible to explore the fraction of individuals in the whole nation, or in specific regions, that visited certain locations.
Instructions for Fig. 3
While exploring the graph above, one observes that northern regions (e.g., Lombardia, Emilia-Romagna, Piemonte) are faster in enforcing the lockdown than southern regions (e.g., Campania, Abruzzo). This fact is not surprising considering that the pandemics stroke harder in the north of the country, so the risk there might be perceived stronger than in the south. Moreover, some partial lockdowns occurred in the northern regions the national one.
As the lockdown was enforced, visiting certain areas were forbidden, except for justified reasons. To quantify the level of compliance with the lockdown, in the map below, we show the fraction of people that committed an infraction, defined as a visit of POIs forbidden by the lockdown: transportations or leisure POIs. It should be remarked that an infraction is such only after the lockdown has been declared.
We see that this fraction decreases dramatically from a value around 0.4 before the lockdown a value around 0.12 during the lockdown. This implies that the level of compliance with the rules has been progressively increasing. This decrease is a good indication that lockdown measures have been followed by the population at the country level, at least till the end of March 2020. Still, one can appreciate deviations from one region to another. We will show you in forthcoming reports how the situation evolved afterwards. Stay tuned!