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Rapid Assistance in Modelling the Pandemic: RAMP

The Royal Society has used its convening power to support efforts to model the Coronavirus (COVID-19) pandemic and guide the UK’s response.  The Rapid Assistance in Modelling the Pandemic (RAMP) initiative has brought modelling expertise from a diverse range of disciplines to support the pandemic modelling community already working on Coronavirus (COVID-19). 

An initial call for volunteers led to an overwhelming response with 1800 individuals and teams offering to help. 

RAMP is designed to; provide support for existing research groups; create new models or insights that can be used to inform the work of the Government’s scientific advisors, through data science-based approaches; apply knowledge from related epidemiology domains; and triage incoming literature to ensure effective information flows.

The goal of RAMP was to enhance modelling capacity in time to create a clearer understanding of different exit strategies from the current lockdown. RAMP operates beside Data Evaluation and Learning for Viral Epidemics (DELVE), a multi-disciplinary group, convened by the Royal Society, to support a data-driven approach to learning from the different approaches being taken in other countries to tackle the pandemic and SET-C a group drawing on the expertise of our Fellows and others to respond to requests for rapid science advice on topics relevant to tackling the pandemic.

The RAMP initiative was initially set up to run until July but many of the volunteers and projects are still making significant contributions and will continue to do so.

See the latest update.

Previous updates

29 April 2020:  Update from Peter Bruce FRS

RAMP Steering Committee      (22 October 2020)

  • Mike Cates (Chair) FRS FRSE, Lucasian Professor of Mathematics at the University of Cambridge
  • David Abrahams FRSE, Rosthchild Professor of Mathematical Sciences, and Director of Isaac Newton Institute, University of Cambridge
  • Graeme Ackland FRSE, Professor of Physics at the University of Edinburgh
  • Mike Batty FRS CBE FBA, Bartlett Professor of Planning at University College London
  • Mark Birkin, FAcSS, FRGS, Professor of Spatial Analysis and Policy, University of Leeds
  • Peter Bruce FRS, Wolfson Professor of Materials at the University of Oxford
  • Philip Dawid FRS, Emeritus Professor of Statistics, University of Cambridge
  • Julia Gog OBE, Professor of Mathematical Biology at the University of Cambridge and member of the Scientific Pandemic Influenza Group on Modelling (SPI-M)
  • Alain Goriely FSIAM, FIMA, Professor of Mathematical Modelling, University of Oxford
  • Deirdre Hollingsworth, Professor and Senior Group Leader, Big Data Institute, University of Oxford
  • Kostas Kavoussanakis, Group Manager, EPCC, University of Edinburgh
  • Philip Maini FRS, Professor of Mathematical Biology, University of Oxford
  • Cath Noakes OBE, Professor of Environmental Engineering for Buildings at the University of Leeds
  • Kenji Takeda, Director of Health and AI Partnerships (Academic), Microsoft Research, Cambridge