IMMUNE is a nine-month project funded by the AHRC (UKRI COVID-19 Research Call) in collaboration with Loughborough University.
The purpose of this research project is to apply a user-centred design approach to conduct research that contributes to our understanding of immunity and vaccination passport services as part of the UK's COVID-19 exit strategy.
These immunity or vaccination passports would allow individuals who have antibodies of the SARS-COV-2 to return back to work, travel or socialise without restrictions. Their use has formed part of many countries' exit plans. Yet, there is a dispute among scientists, policymakers and the public that such interventions are based on many uncertainties that could put public health at risk, infringe privacy, and lead to inequalities in society.
To better understand this phenomenon, we will engage with key stakeholders to address the following two questions:
- What are the possible unintended consequences and risks of immunity passports?
- What are the key stakeholders' requirements, resources, AI technologies and processes needed in the design of services around immunity or vaccination passports in order to mitigate any unintended consequences?
Our approach will involve interviews, surveys, focus groups and participatory design workshops. Key deliverables will be specifications for service design including blueprints, user journey maps and systems modelling.
Meet the Principal Investigator(s) for the project
Dr Isabel Sassoon
- Dr Isabel Sassoon is a Lecturer in Computer Science at Brunel University. Before joining Brunel Isabel was Research Associate on the CONSULT (Collaborative Mobile Decision Support for Managing Multiple Morbidities), an EPSRC funded project in the Department of Informatics in King’s College London. This project developed a collaborative mobile decision-support system to help patients suffering from chronic diseases to self-manage their treatment, by bringing together and reasoning with wellbeing sensor data, clinical guidelines and patient data. Prior to that Isabel was Teaching Fellow in the Department of Informatics in King’s College London, primarily on the Data Science MSc.
Isabel's research interests are in data-driven automated reasoning, and its transparency and explainability. Her PhD research developed a computational argumentation based system to support the appropriate selection of statistical model given a research objective and available data. Her current research continues to explore how computational argumentation can assist in model explainability and trust.
Prior to joining King's College London Isabel worked for more than 10 years as a data science consultant in industry, including 8 years in SAS UK. Isabel read Statistics, Operations Research and Economics at Tel Aviv University and received her Ph.D. in Informatics from King's College London.