Explaining the Initial Spread of COVID-19 using Mobile Positioning Data: a Case Study

This work provides an analysis on the potential of aggregate and anonymised mobility data from mobile phones to explain the recent COVID-19 outbreak in Europe. The data were processed by the European Commission in collaboration with EU Mobile Network Operators (MNOs) to improve the quality of modelling and forecasting for the pandemic at EU level. Connectivity matrices derived from MNOs at EU scale can help the understanding of the initial dynamics of the spread. This work is expected to provide input to epidemiological modelling in informing policies on de-escalation of control measures and recovery. Connectivity data between administrative areas can also be used to estimate impacts and spread of future outbreaks. A case study of France shows that mobility alone can explain from 52% up to 92% of the initial spread of the virus, while there is no effect before the outbreak, and has a slow decay effect after lockdown measures are effective. It also emerges that internal mobility is more important than mobility across geographical departments.