The fight against the COVID-19 pandemic still involves many struggles and challenges. The greatest challenge that most governments are currently facing is the lack of a precise, accurate, and automated mechanism for detecting and tracking new COVID-19 cases. In response to this challenge, this study proposes the first blockchain-based system, called the COVID-19 contact tracing system (CCTS), to verify, track, and detect new cases of COVID-19. The proposed system consists of four integrated components: an infection verifier subsystem, a Mass Surveillance subsystem, a P2P mobile application, and a blockchain platform for managing all transactions between the three subsystem models. To test the performance of the proposed system, CCTS has been simulated and tested against a created dataset consisting of 300 confirmed cases and 2539 contacts.  The evaluation results proved that the proposed blockchain-based system achieved 75.79% accuracy in recognizing persons in contact with COVID-19 patients. This result can be considered a unique one compared with other systems in the literature. The simulation results also demonstrated the success of the proposed system in performing self-estimation of infection probabilities and sending and receiving infection alerts in P2P communications in crowds of people by users. The new system could support governments, health authorities, and citizens in making critical decisions regarding infection detection, prediction, tracking, and avoiding the COVID-19 outbreak. Moreover, the functionality of the proposed CCTS can be proper to work against any other similar pandemics in the future.

Keywords: Blockchain technology,  COVID-19 pandemic, Infection data communication, Ubiquitous computing