Covid-19 vs Mobility: what can data tell us?

Covid-19 is changing our lifestyles, but can mobility data show these changes? What are the major changes in our movements? We focuse on the subject using the Open Data available.

French Mobility strongly impacted in Paris
French mobility strongly impacted by Covid-19 – Photo by David Castellón on Unsplash

Mobility data: where do they come from?

I dare to answer “from your pocket”… Because, yes: It all starts with your smartphone and the famous position tracking.

So when you activate the “location history” option, Google stores and can use your phone’s location. Google makes this information available to the general public to help health authorities in particular in their decision-making. As for Apple, they follow a similar process by making public the route requests made through their Maps application. In both cases, it all starts with your phone.

What about data privacy?

At this point, you are raising your eyebrows a bit. Indeed, the point-to-point monitoring of your movements is personal information, including within the meaning of the GDPR regulations. This is why the 2 digital giants have done things with great care. First, you have the choice: Activating the famous position history option is entirely up to you. Likewise, you can delete the history at any time. Second, both Google and Apple respect your privacy and anonymize information. Concretely, this means that it is impossible to associate a location or a route search with a person.

Where can you find mobility data?

Google and Apple publish this information as open data. They produce flat files (csv) which include data aggregated to the daily grid, by country, sometimes by region and completely anonymized. In both cases, the information represents a variation from a reference period.

For Apple, January 13, 2020 is the benchmark. The available data shows the daily variation of route searches on Maps compared to this baseline.

For Google, same way but it is the movement trends which is observed. The baseline period extends over the five weeks between January 3 and February 6, 2020. Thus, this open data information provides information on variations compared to a normal value observed on the baseline days.

What can we learn from covid-19 mobility data?

We used Google data to deepen our analysis. Indeed, they propose a great range of information across different categories of places.Thus, we access 6 categories:

  • Retail and recreation
  • Supermarkets and pharmacies
  • Parks
  • Public transport
  • Workplaces
  • Residential.

We focused our analysis on France and used Drop to Kibana to get some informative charts.

For example, we intuitively know that workplaces are much less crowded than usual, including outside lockdown periods. The graph below confirms this intuition: during the 1st lockdown, the workplaces attendance fell by up to -90%. Moreover, the post lockdown period has never restored nominal level. Actualy, the Google data accross workplaces movement trends from shows an average drop of over 50% with a new accentuation at the approach of October 30 following the incentives for extended teleworking.

Google mobility data graph - variation in frequentation of workplaces in France
Movement trends accross French Workplaces analysis by

Consequently, we find a completely reversed trend in frequentation of places of residence as shown in the graph below.

Google mobility data graph - variation in frequentation of residential places in France
Movement trends accross French Residential places analysis by
Google mobility data graph - variation in frequentation of recreation or retail places and parks

What about leisure?

The French have largely shunned places dedicated to leisure or retail, including from the month of May.

Remarkable point, a real boom in the use of green spaces with parks and gardens stormed out of the first confinement. Obviously, the population was keen to breathe outdoor. Covid-19 mobility data indicates record attendance levels accross gardens and green spaces during the summer period.

In conclusion, the Covid-19 mobility open data makes it possible to accurately assess the trends. Their use is very simple: organized in a flat file, this data is large with more than 3 million records for the worldwide dataset. A good opportunity to use powerful tools like Drop to Kibana to make this data tell you all.

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