A new online tool from Oxford researchers uses mobile phone data to help tackle Covid-19. Data from mobile phones is being used to understand and predict the impact of the UK’s Covid-19 social distancing measures on population movements nationwide, thanks to a new online tool developed by a team of AI and big data researchers at the University of Oxford.
The Oxford Covid-19 Impact Monitor has already revealed how life in the UK has changed since the Coronavirus outbreak:
19 million Britons are the most at risk of Covid-19 because of age and underlying health conditions
- Population movement has dropped by 98% since the beginning of March
- 55% of Britons stayed at home on Easter Monday
- Despite a surge in Covid-19 hospital admissions, overall hospital footfall has fallen by 80%
- The least busiest time to visit a supermarket is Tuesday at 9 am
- 19 million Britons are the most at risk of Covid-19 because of age and underlying health conditions
- The flow of people between regions in the UK has tumbled by 76%
To allay privacy concerns the Oxford Covid-19 Impact Monitor only uses anonymised and aggregated mobile phone location data. This GDPR-compliant data is then used to power interactive digital dashboards that can help policymakers, clinicians and the general public to understand better the impact of Covid-19 on the NHS and the wider community. The online dashboards are free and publicly available, together with key insights from the data. Analyses can be carried out at different degrees of geographic detail, including at the local and regional levels, and also for specific NHS hospital catchment areas.
Getting insights from big data is key if the UK is effectively to fight coronavirus, whilst at the same time making costly measures such as social distancing work as efficiently as possible
Commenting on the launch of the new tool, Dr Adam Saunders says: 'The monitoring of population movements in response to the Covid-19 pandemic has received considerable attention following its use in China, South Korea and Singapore, the countries where the virus impacted earliest. The team came together to do what we could to help tackle the challenge facing the UK through the use of ethical big data analytics for the public good.'
Dr Matthias Qian adds: 'Getting insights from big data is key if the UK is effectively to fight coronavirus, whilst at the same time making costly measures such as social distancing work as efficiently as possible. Fully anonymised and aggregated mobile phone location data provides a responsible approach for revealing important insights for the NHS, the government and the wider public, which can help save lives.'
The new tool was developed by a team from across the University of Oxford led by Dr Adam Saunders (SKOPE, Department of Education) and Dr Matthias Qian (Department of Economics). Team members include Daniel Pesch (Saïd Business School), Dr Steven Reece (Department of Engineering Science), Dr Won Do Lee (Transport Studies Unit, School of Geography and the Environment), Professor Renaud Lambiotte (Mathematical Institute) and Lucas Kruitwagen (School of Geography and the Environment).
Project partners include:
- Oracle - supporting the online tool with cloud-based high performance computing
- Cuebiq - providing anonymised and aggregated data from opted-in users via its Data for Good programme
- CKDelta - providing a wide array of anonymised and aggregated data
- Facebook’s Data for Good programme – which provided the UK population density map base layer, built with satellite imagery and census data, for validation purposes