4.8 Article

A Framework for Infectious Disease Monitoring With Automated Contact Tracing-A Case Study of COVID-19

期刊

IEEE INTERNET OF THINGS JOURNAL
卷 10, 期 1, 页码 144-165

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2022.3199216

关键词

Automated contact tracing; biomedical telemetry; COVID-19; e-health; health monitoring; infectious disease monitoring; telemedicine; wearable sensors

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Deadly infectious diseases have occurred throughout human history, and despite advanced healthcare systems, COVID-19 has caused over six million deaths worldwide as of July 27, 2022. Contact tracing is a tool used to monitor and control disease spread, but manual contact tracing is challenging and time-consuming. Many digital contact tracing applications have been developed globally, and this study reviews the current technologies, proposes an integrated system for contact tracing using COVID-19 as a case study, and introduces four main modules to evaluate users' risk and provide notifications. The system also integrates web-based information and screening tools to increase its adoption rate.
Throughout human history, deadly infectious diseases emerged occasionally. Even with the present-day advanced healthcare systems, the COVID-19 has caused more than six million deaths worldwide (as of 27 July 2022). Currently, researchers are working to develop tools for better and effective management of the pandemic. Contact tracing is one such tool to monitor and control the spread of the disease. However, manual contact tracing is labor-intensive and time-consuming. Therefore, manually tracking all potentially infected individuals is a great challenge, especially for an infectious disease like COVID-19. To date, many digital contact tracing applications were developed and used globally to restrain the spread of COVID-19. In this work, we perform a detailed review of the current digital contact tracing technologies. We mention some of their key limitations and propose a fully integrated system for contact tracing of infectious diseases using COVID-19 as a case study. Our system has four main modules-1) case maps; 2) exposure detection; 3) screening; and 4) health indicators that take multiple inputs like users' self-reported information, measurement of physiological parameters, and information of the confirmed cases from the public health, and keeps a record of contact histories using Bluetooth technology. The system can potentially evaluate the users' risk of getting infected and generate notifications to alert them about the exposure events, risk of infection, or abnormal health indicators. The system further integrates the Web-based information on confirmed COVID-19 cases and screening tools, which potentially increases the adoption rate of the system.

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