Winner: Ming Tang is the Chief Data and Analytics Officer for NHS England and NHS Improvement
Ming created the Covid Data store for NHS England and was a stand-out entry because at a critical point she was able to combine data analytics, create new data sets and curate and mobilise the power of AI to fil a COVID demand and supply chain abyss. This helped create one version of the ‘on the NHS ground truth’. This was at a time in the pandemic when all decision makers had their own opinions about demand, PPE, medicines, and critical care staff capacity. Ming is not only a supreme data scientist but demonstrated significant powers of persuasion to bring multiple stakeholders together and create a team in a time of crisis.
Runner up: Ruth Studley, Head of Analysis on the COVID-19 Infection Survey, ONS
The COVID-19 Infection Survey (CIS) provides vital information to help the UK’s response to the pandemic. Ruth helped design and continually improve the survey to ensure that the data was presented in near real-time and was easily accessible to the public. By creating a cohort of 500,000 people who consented to have their data used for research, this work made a significant contribution to public understanding during the pandemic. The survey has really contributed to building public trust in the use of personal health data.
Runner up: Silvia Ottaviani, Senior Lecturer in molecular cell biology, Nottingham Trent University
Silvia’s work involved using AI and other data from the UK and Italy to accelerate the identification of baricitinib as a novel antiviral drug resulting in a 71% reduction in deaths observed in moderate-severe SARS-CoV-2 pneumonia (this included a large elderly cohort). The impressive nomination also included practical examples of the ways in which Silvia inspired other women and girls into STEM roles around this work. She delivered this project over and above her day job and carried on working to deliver it during her maternity.