Providing COVID-19 expertise to the UK government

The Turing-RSS Health Data Lab delivered invaluable insights to the UK Health Security Agency throughout the pandemic

Last updated
Wednesday 13 Jul 2022

The Turing-RSS Health Data Lab, a partnership established in August 2020 between the Turing and the Royal Statistical Society, has provided invaluable insights to the government’s UK Health Security Agency, which is responsible for public health protection in the UK.

The Lab aims to develop statistical and machine learning techniques to answer policy-relevant questions about COVID-19. It is made up of over 35 people in research, leadership and operational roles from more than 10 institutes, including Imperial College London, MRC Harwell and the University of Oxford.

“The Alan Turing Institute and the Royal Statistical Society came together at pace in response to the COVID-19 pandemic, providing world-class independent research and modelling expertise to the UK government.”

Johanna Hutchinson, Director of Analytics and Data Science, UK Health Security Agency

In December 2021, Lab researchers published a paper in Nature Microbiology describing a statistical framework that combines multiple sources of COVID-19 test data to provide more accurate estimates of local virus prevalence. This was followed in February 2022 by a statistical analysis from the Lab, published in The Lancet Regional Health, which found that deprived areas in England with higher proportions of non-White people were associated with higher COVID-19 infection rates. However, the strength of this association varied over the course of the pandemic and for different ethnic subgroups, highlighting the importance of continual monitoring when developing policies aimed at eliminating health inequalities.

Other work at the Lab has included a project looking at the potential of diagnosing COVID-19 and other diseases by acoustically analysing someone’s speech or coughs, and a statistical model that uses incomplete COVID-19 test data to estimate (‘nowcast’) the total number of positive tests. Meanwhile, a recent paper describes the Lab’s overarching approach to statistical modelling, setting out a framework that will allow other research teams to rapidly build effective, data-driven models in response to future health emergencies.

“The partnership has played a highly valuable role in developing and further enhancing the data science and advanced analytical capabilities within the UK Health Security Agency, both in responding to COVID-19 and in tackling new and existing threats to UK health.”

Johanna Hutchinson, Director of Analytics and Data Science, UK Health Security Agency

Further reading:

This piece first appeared in The Alan Turing Institute’s Annual Report 2021-22
Top image: Sergey Zaykov / Shutterstock


Professor Peter Diggle

Distinguished Professor, CHICAS, Lancaster University and Steering Group Mentor, RSS COVID-19 Taskforce

Ali Marsh

Senior Programme Manager, Health and Medical Sciences (Maternity Leave)

Dr Brieuc Lehmann

Assistant Professor (University College London) and member of the Turing-RSS Lab