New funding for national consortium to model COVID-19 pandemic predictions

A national consortium bringing together modellers to produce rigorous predictions for the COVID-19 pandemic and advise UK government bodies will receive £3 million funding from UK Research and Innovation (UKRI).

The JUNIPER consortium (‘Joint UNIversities Pandemic and Epidemiological Research’) brings together leading mathematical and statistical modellers from seven UK universities, including researchers Drs Ellen Brook Pollock , Hannah Christensen and Leon Danon from the University of Bristol.

They are developing and using bespoke models to provide predictions and estimates on key questions about the COVID-19 pandemic. These results feed regularly into SPI-M (Scientific Pandemic Infleunza Group on Modelling), the modelling group that provides evidence to the Scientific Advisory Group for Emergencies (SAGE) and the wider UK government.

Examples of modelling the consortium provides to government includes:

  • Understanding how new variants are spreading across the UK and developing statistical models to determine whether a new variant is causing more hospitalisations or deaths.
  • Forecasting and providing real-time estimates of the R value, using data from many sources such as Pillar 1 and 2 testing, hospital data and mobility data. They are currently providing eight of 12 models contributing real time R estimates that go from SPI-M to SAGE each week.
  • Modelling the effectiveness of different testing strategies on virus transmission and suppression, and modelling the effect of vaccinations and predicting outcomes from different scenarios of how to ease lockdown restrictions.

Dr Ellen Brooks Pollock, co-investigator of the consortium, member of SPI-M, SPI-B and SAGE-subgroup on children and schools and Senior Lecturer in Infectious Disease Mathematical Modelling at the University of Bristol, said: "It’s exciting to be part of the JUNIPER consortium. Many of the JUNIPER researchers have been working together throughout the pandemic, and this funding award will support those collaborations.

"The work is fast-paced and dynamic, and being part of a group of world-class modellers means that we can draw on a range of expertise. We are recruiting three further postdocs to join the Bristol JUNIPER team, so do get in touch if you are interested."

Dr Leon Danon, member of SPI-M and SAGE-sub-group on social care and Associate Professor in Infectious Disease Modelling and Data Analytics from the University of Bristol, and the Alan Turing Institute , added: "This consortium formalises a long-standing collaboration between the member universities. The funding not only enables us to respond rapidly and robustly to pressing policy questions but also helps develop the scientific legacy of the Covid pandemic."

The consortium, co-led by Professors Julia Gog from the University of Cambridge and Matt Keeling from the University of Warwick, is funded as part of UKRI’s COVID-19 Agile Call , which has so far invested more than 150 million in over 400 projects and consortia to address the impacts of the COVID-19 pandemic.

Professor Charlotte Deane, COVID-19 Response Director at UKRI, said: "This consortium enables disease modellers to pool their expertise nationally to increase the scale, speed and quality of their models of policy options and predictions for the pandemic. They’ll provide cutting-edge evidence about the pandemic into the UK government’s decision-making."

The consortium will also proactively generate new model-based predictions and develop the necessary methodology as part of a horizon-scanning process.

The consortium plan to make their models open-source, so scientists worldwide can access them and benefit.

The research groups in the consortium are based at seven universities: University of Bristol, University of Cambridge, University of Exeter, Lancaster University, The University of Manchester, University of Oxford and University of Warwick.

They will work closely with many other organisations and research teams active on COVID-19 research including the Alan Turing Institute , the Royal Statistical Society , Health Data Research UK , Public Health England , the Royal Society’s ’RAMP’ initiative and the Isaac Newton Institute for Mathematical Sciences.


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