SMARTPHONE APPLICATIONS FOR CONTACT TRACING IN COVID-19 EPIDEMIC: A SYSTEMATIC REVIEW - Saleem, Fouad Salim; Al-Mejibli, Intisar (Journal of Al-Qadisiyah for Computer Science and Mathematics, 2021)
The great spread of the COVID-19 Pandemic and its effect on lifestyle around the world has led countries and organizations to accelerate the design or use of mobile health systems and applications to tackle and monitor the outbreak. Digital contact tracing applications have been proposed to automatically warning individuals at risk of infection and exposure. This systematic analysis discusses the various types of mechanisms and systems used in applications for digital contact tracing including Centralized, Decentralized, or Hybrid, in addition to, the used communication technologies such as Bluetooth, GPS, WiFi, and others, with a focus on user privacy and the efficiency of dealing with the extracted data. Four databases were scanned (IEEE Xplore, ScienceDirect, Web of Science, and PubMed) between 2015 and 2020. To review the collected 636 papers, precise exclusion criteria and selection strategies were applied. Only seven papers have been thoroughly analyzed and included in this study. The results in all papers have been presented to identify gaps and issues to supply an overview of the main aspects that need to be included and resolved in mobile applications that will be built to effectively restrict the spread of this pandemic and preserve full user privacy.