Using data to identify at-risk groups: limitations and lessons from COVID-19

Abstract

Lessons learned from a review of the UK COVID-19 vaccination programme included the need for improved data sharing. Achieving this will require a sensitive balance between existing data protection legislation, investment in the replacement of legacy systems and an appreciation of the variation in nomenclature used in different sectors (and even within the same sector). Future pandemics may affect different population groups, and the public and media need to understand the definitional and data constraints that could impact the identification of ‘at-risk’ groups. This is particularly important for any associated vaccination rollout. This article illustrates the complexities that can be involved in these data processes, including definitional practicalities relating to certain potential at-risk groups, existing limitations on available data, the need to ask the right questions, the use of data by the media and pressure groups and the importance of sound data. The authors believe that the points raised can contribute to the ongoing debate.