Two Somerville Fellows have helped to create a new tool which uses mobile phone data to better understand and predict the impact of the UK’s Covid-19 social distancing measures.
The online tool was created by a team of AI and big data researchers at Oxford University, led by Dr Adam Saunders (SKOPE, Department of Education) and Dr Matthias Qian (Department of Economics).
The Oxford Covid-19 Impact Monitor takes anonymised mobile phone location data and uses it to power a set of freely available interactive digital dashboards on https://oxford-covid-19.com/ that visualise the impact of the virus and associated social distancing measures on the population.
Analysis can be carried out at local and regional levels, and even for specific NHS hospital catchment areas. The insights gleaned will help policymakers, clinicians and the general public to understand the impact of Covid-19.
The tool has already revealed that population movement has dropped 98% since the start of March, showing that the population are sticking to government advice.
It has also identified that 55% of Britons stayed at home on Easter Monday, that hospital footfall has fallen 80% despite a surge in admissions, and that the least busy time to visit the supermarket to do your shopping is at 9am on a Tuesday.
“Big data offers the huge advantage of providing real-time tracking of how collective behaviour evolves,” said Professor Lambiotte.
“While there is a delay of at least several days to other information such as number of infections, mobility can be tracked on a daily basis.”
“This instant data will be essential when it comes to exiting from confinement measures and of navigating the country back to normality.”