Data donation of individual shopping data to help predict the occurrence of disease: A pilot study linking individual loyalty card and health survey data to investigate COVID-19

Introduction & BackgroundPrevious studies have found shopping data could increase the predictive accuracy of disease surveillance systems and illuminate behavioural responses in the self-management of symptoms of disease. Yet, accessing individual sales datasets for linkage to health datasets is challenging, and the recruitment of appropriate sample sizes for medical research has been limited. Objectives & ApproachObjectivesCollect and link individual health data to individual shopping data to investigate COVID-19. Assess the feasibility of scaling-up this method, and use the collected data to investigate using loyalty card data in machine learning (ML) models for disease. MethodsBased on recommendations on the public’s preferences for data donation a new protocol was designed for collecting, linking and analysing shopping and health data. Participants were requested to use the Tesco Clubcard website data portability function to share their loyalty card data and complete an online health survey. An exploratory data analysis was conducted on the linked dataset. Participants were recruited online (18/01/2022 to 04/02/2022) with a recruitment target of 200. Relevance to Dig