COVID-19 Contact Tracing and Detection-Based on Blockchain Technology

Abstract

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 investigate the performance of the proposed system, CCTS has been simulated and tested against a created dataset consisting of 300 confirmed cases and 2539 contacts. Based on the metrics of the confusion matrix (i.e., recall, precision, accuracy, and F1 Score), the detection evaluation results proved that the proposed blockchain-based system achieved an average of accuracy of 75.79% and a false discovery rate (FDR) of 0.004 in recognizing persons in contact with COVID-19 patients within two different areas of infection covered by GPS. Moreover, 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 infection probability results have been calculated using the binomial distribution function technique. This result can be considered unique compared with other similar systems in the literature. 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 adapted to work against any other similar pandemics in the future.

A Cross Platform Contact Tracing Mobile Application for COVID-19 Infections using Deep Learning

“…For instance, blockchain technology has been proposed to preserve privacy during contact tracing for COVID-19 pandemic to gain trust by users [25][26] [27]. According to [26], it was reported that blockchain technology was able to detect unknown cases of COVID-19. The application was also capable of enabling individuals to use the mobile application to predict the probabilities of being infected.…”

Recent Advances of Blockchain and Its Applications

“…Contact tracing requires people to share their private contact history, sometimes even including sensitive information such as GPS coordinates or medical history [202,203] . Most initial attempts of blockchain-powered contact tracing approaches are of high level and treat blockchain naively as external storage or with no simulation provided to illustrate the effectiveness, such as BeepTrace [204] , Arifeen et al [205] , and Choudhury et al [206] Hasan et al [207] proposed to use blockchain to record participants' GPS coordinates and trigger proof of location to conduct contact tracing and risk alert. In their proposed system, external oracles are adopted to conduct contact tracing algorithm, and blockchain works as a bridge from external oracles to involved parties, including testing center and patients.…”

A blockchain-based infection tracing and notification system by non-fungible tokens

“…Although the implementation demonstrates the feasibility of the proposed approach, the use of zero-knowledge scheme could determine high drain of battery in a real life scenario. In [23] an integrated contact tracing system is proposed to verify, track, and detect new cases of COVID-19. The proposed system consists of three components: an infection verifier subsystem, a mass surveillance subsystem and a P2P mobile plus a blockchain employed for managing all transactions between the three subsystems.…”