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dc.contributor.authorTorky, Mohamed
dc.contributor.authorGoda, Essam
dc.contributor.authorSnášel, Václav
dc.contributor.authorHassanien, Aboul Ella
dc.date.accessioned2022-04-13T13:32:59Z
dc.date.available2022-04-13T13:32:59Z
dc.date.issued2021
dc.identifier.citationInformatics. 2021, vol. 8, issue 4, art. no. 72.cs
dc.identifier.issn2227-9709
dc.identifier.urihttp://hdl.handle.net/10084/146045
dc.description.abstractThe 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.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesInformaticscs
dc.relation.urihttps://doi.org/10.3390/informatics8040072cs
dc.rights© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectblockchain technologycs
dc.subjectCOVID-19 pandemiccs
dc.subjectinfection data communicationcs
dc.subjectubiquitous computingcs
dc.titleCOVID-19 contact tracing and detection-based on blockchain technologycs
dc.typearticlecs
dc.identifier.doi10.3390/informatics8040072
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume8cs
dc.description.issue4cs
dc.description.firstpageart. no. 72cs
dc.identifier.wos000738705200001


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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.