Delineating the Privacy Concerns of Covid Tracing Applications: A Mixed Method Analysis

As Covid pandemics expanded over the globe, governments implemented a series of technological measures to prevent the disease's spread. The development of Covid tracing applications was one of these measures. In this study, we employed bibliometrics and cluster-based content analysis to determine the most significant entities and research topics in 329 Scopus-indexed papers. Additionally, we identified significant privacy concerns posed by the Covid tracking apps, which gather, store, and analyse data in partnership with large technology corporations using proximity measuring technologies, artificial intelligence, and blockchain. We examined the seven key privacy threats identified in our study.  These privacy risks include anti-democratic and discriminatory behaviors, politicization of care, derogation of human rights, technogovernance, citizen distrust and refusal to adopt, citizen surveillance, and mandatory legislation of the apps' installation. Finally, sixteen research gaps were identified. Then, based on the identified theoretical gaps, we recommended fourteen prospective study strands. Theoretically, this study contributes to the growing body of knowledge about the ethics and privacy of digital health.