COVID-19 Modelling Consortium: quantitative epidemiological predictions in response to an evolving pandemic

Since the beginning of the COVID-19 pandemic in early 2020, mathematical and statistical modelling have been used to provide estimates of the epidemic in the UK, and to make short- and long-term predictions about the impact of interventions. The teams of epidemiological modellers and statisticians in our JUNIPER (Joint UNIversity Pandemic Epidemiological Research) consortium represent a core of committed and experienced university research groups that have dedicated themselves since February 2020 to generating predictions, forecasts and insights. These findings feed directly into the Scientific Pandemic Influenza Group on Modelling (SPI-M) and the Scientific Advisory Group for Emergencies (SAGE), both of whom advise the UK government on scientific matters relating to the UK's response to the pandemic. As part of SPI-M this group has brought together a range of analyses to underpin diverse policy decisions including early estimates of the scale of an uncontrolled epidemic, reasonable worst-case scenarios and the impact of reopening schools. Moving forward, critical research gaps remain unaddressed, and further translational work must be conducted to generate the necessary insights. The requested funding will ensure these key groups, with their extensive experience of delivering science for policy and deep understanding of this outbreak, will be able to continue and expand their activities. The Juniper consortium members will continue to respond to rapid requests from the UK government via SPI-M and SAGE, including providing weekly forecasts of the reproductive number R and growth rate in the UK and predictions of the likely impact of policy decisions and interventions. The research teams will be flexible and adaptive to the changing phases of the epidemic, and will proactively consider novel methodology, analysis or modelling that is required, as well as horizon scan the impact of new scientific findings and how this will impact on current and future modelling. The programme of work will address a core set of eight overarching questions that the consortium has identified as being important over the next 12-18 months: 1. How to best address issues around the storage, curation, and processing of the growing number of COVID-related data streams 2. Improving statistical and computational fundamentals for outbreaks 3. Refining methodology for the detection of hotspots or regions in need of greater control 4. Developing bespoke methods to analyse and model Surveillance, Test and Trace 5. Refining methodologies to determine risks posed by structured environments such as workplaces, care homes, hospitals, schools, universities 6. Producing realistic individual-scale modelling of contemporary social interactions 7. Implication of finer-scale individual-level characteristics and impacts of short- and long-term immunity in models. 8. Detailed retrospective analysis of the first wave. Our consortium will embed these scientific activities within an open and collaborative framework, including considerable public outreach so that scientific assumptions and findings are effectively communicated. Our consortium will be outward-facing and inclusive, helping to add value to a range of existing and new COVID-19 activities. We aim to build national capacity and the proposed programme will also contribute to training the next generation of applied epidemiological modellers.