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Royal Society convenes data analytics group to tackle COVID-19

17 April 2020

We are at a crucial juncture in the UK’s response to the COVID-19 pandemic. There is a pressing need to analyse emerging data from countries around the world to identify the most important factors that can help slow the spread of the virus and help find long-term solutions to the pandemic. Science has helped to guide the response to the COVID-19 pandemic and there is more the community can do to complement existing efforts. 

DELVE: Data Evaluation and Learning for Viral Epidemics is a multi-disciplinary group, convened by the Royal Society, to support a data-driven approach to learning from the different approaches countries are taking to managing the pandemic. This effort has been discussed with and welcomed by Government, who have arranged for it to provide input through SAGE, its scientific advisory group for emergencies. 

DELVE will contribute data driven analysis to complement the evidence base informing the UK’s strategic response, by:

  • Analysing national and international data to determine the effect of different measures and strategies on a range of public health, social and economic outcomes
  • Using emerging sources of data as new evidence from the unfolding pandemic comes to light
  • Ensuring that the work of this group is coordinated with others and communicated as necessary both nationally and internationally

This work will be carried out by three cross-disciplinary groups:

  • Working group: a team of data scientists and subject-matter experts to carry out data analysis, synthesis of results and rapid review
  • Advisory group: a wide group of experts to provide review and feedback
  • Committee: a high-level expert group to oversee the work and communicate findings to the Government’s Chief Scientific Advisor and his networks in government

DELVE on GitHub

Cross-disciplinary groups

Find full details on GitHub.

The Committee includes the following individuals:

Venki Ramakrishnan FRS (Chair), President of the Royal Society
Charles Bangham FMedSci FRS, Professor of Immunology, Faculty of Medicine, Imperial College London
Paul Edelstein, Emeritus Professor CE of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania
Nigel Field (Chair of Working Group), Director of the Centre of Molecular Epidemiology and Translational Research at the Institute for Global Health, University College London 
Tim Gowers FRS, Royal Society Research Professor, Centre for Mathematical Sciences, University of Cambridge
Bryan Grenfell FRS, Professor of Ecology and Evolutionary Biology and Public Affairs, Princeton
Demis Hassabis FREng FRS, Co-founder and CEO of DeepMind (serving in a personal capacity)
Anne Johnson FMedSci, Professor of Infectious Disease Epidemiology at University College London and Vice President of the Academy of Medical Sciences
Daniel Kahneman, Professor of Psychology and Public Affairs Emeritus at the Woodrow Wilson School, the Eugene Higgins Professor of Psychology Emeritus at Princeton University, and a fellow of the Center for Rationality at the Hebrew University in Jerusalem
Neil Lawrence (Working Group), Professor of Machine Learning at the University of Cambridge
Julie Maxton, Executive Director, Royal Society
Lalita Ramakrishnan FMedSci FRS, Professor of Immunology and Infectious Diseases and Head of Molecular Immunity Unit, Department of Medicine, University of Cambridge   
Sylvia Richardson FMedSci, Chair of Biostatistics and Director of the MRC Biostatistics Unit, University of Cambridge, President Elect of the Royal Statistical Society
Devi Sridhar, Professor of Global Public Health, University of Edinburgh 
Nick Stern FBA FRS, IG Patel Professor of Economics and Government, Chairman of the Grantham Research Institute on Climate Change and the Environment and Head of the India Observatory at the London School of Economics
Yee Whye Teh (Working Group), Professor at the Department of Statistics of the University of Oxford (seconded from his part time role as a Research Scientist at DeepMind)

Working Group

  • Alison Simmons
  • Aziz Sheikh
  • Carol Propper
  • Devi Sridhar
  • Frank Kelly
  • Majid Ezzati
  • Neil Lawrence
  • Paul Edelstein
  • Peter Diggle
  • Rachel Griffith
  • Rupert Lewis
  • Tim Besley
  • Yee Whye Teh
  • Nigel Field
  • Simon Burgess

Action Team

  • Alex Archibald
  • Andrei Paleyes
  • Avishkar Bhoopchand
  • Axel Gandy
  • Bobby He
  • Bryn Elesedy
  • Caroline Wagner
  • Chris Chiu
  • David Ellis
  • Doug McNeall
  • Fiona Culley
  • Genevie Fernandes
  • Guy Harling
  • Gwenetta Curry
  • Harpreet Sood
  • Helen Greatrex
  • Inès Hassan
  • Kevin Donkers
  • Lois King
  • Marcel Behr
  • Mark Troll
  • Michael Hutchinson
  • Miqdad Asaria
  • Neil Lawrence
  • Nenad Temasev
  • Niall Robinson
  • Richard Wilkinson
  • Sang Woo (Daniel) Park
  • Sarah Filippi
  • Sheheryar Zaidi
  • Stephen Hansen
  • Thiemo Fetzer
  • Ulrich Paquet
  • Vasco Carvalho
  • Yee Whye Teh
  • Anna Vignoles
  • Tim Clayton

The Royal Society is also convening the Rapid Assistance in Modelling the Pandemic (RAMP) initiative to support efforts to model the Coronavirus (COVID-19) pandemic. RAMP is bringing modelling expertise from areas other than pandemic modelling to support the pandemic modelling community already working on Coronavirus (COVID-19).