ABSTRACT
To control coronavirus disease 2019 (COVID-19), most countries have opted for a containment policy. When a decision of decontainment has to be taken, a question emerges regarding the digital strategy to adopt: Should we track citizens? All of them or only persons who contracted COVID-19? Should we take measures to protect elderly people or people suffering from co-morbidities? Many applications and approaches have been proposed to ensure public safety in the context of COVID-19. In this chapter, we will start by making an inventory of these applications, discuss strategies and technologies adopted, and categorize them. Thereafter we will present an approach consisting in calculating a vulnerability score to propose a solution for protecting people at risk. Then, we will detail the architecture of “uTakeCare, " an open-source application that we have implemented, as well as the method used to calculate the vulnerability score. This method is based on a belief function theory and machine learning techniques. Finally, we will discuss the ethical and legal issues of this application and the methods to be used to address them (e.g., zero-knowledge proof, smart contracts, etc.) as a way to complement general data protection regulation (roadmap to develop personal data) requirements with ethics-by-design and self-sovereign identity solutions. © 2021 Elsevier Inc. All rights reserved.