Statistical and mathematical models are a crucial component in understanding the state and evolution of the COVID-19 pandemic, and for assisting decision makers with the evidence needed to:
- inform and support local and national actions to respond effectively to actual or expected increases in infection levels;
- efficiently manage and deploy resources across the NHS Test and Trace programme, for example to prioritise testing capacity;
- effectively target communications and non-pharmaceutical interventions to local areas expected to be at increased risk of high incidence and prevalence.
The Alan Turing Institute and the Royal Statistical Society (RSS) are partnering on this programme of work to support the Joint Biosecurity Centre (JBC), which is part of NHS Test and Trace, based at the Department for Health and Social Care, by providing an independent source of statistical and mathematical modelling and machine learning expertise to address policy-relevant research questions. The Turing-RSS Lab has been established for one year in the first instance, and will work with JBC to identify and prioritise projects that require reflective thinking to develop and evaluate a solution, but are sufficiently focused so that useful outputs can be obtained within months, thereby filling a current gap between rapid-response consultancy and most existing research funding streams.