Emerging Technologies Used in Health Management and Efficiency Improvement During Different Contact Tracing Phases Against COVID-19 Pandemic

Abstract

Confronted with the COVID-19 health crisis, the year 2020 represented a turning point for the entire world. It paved the way for health-care systems to reaffirm their foundations by using different technologies such as sensors, wearables, mobile applications, drones, robots, Artificial Intelligence (AI), Machine Learning (ML) and the Internet of Things (IoT). A lot of domains have been renovated such as diagnosis, treatment, and monitoring, as well as previously unprecedented domains such as contact tracing. Contact tracing, in conjunction with the emergence, spread, and public compliance for vaccines, was a critical step for controlling and limiting the spread of the pandemic. Traditional contact tracing is usually dependent on individuals ability to recall their interactions, which is challenging and yet not effective. Consequently, further development and usage of automated, privacy-preserving, digital contact-tracing was required. As the pandemic is coming to an end, it is vital to collect and learn the effective used technologies that aided in fighting the virus in order to be prepared for any future pandemics and to be aware of any literature gaps that must be filled. This paper surveys state-of-the-art architectures, platforms, and applications combating COVID-19 at each phase of the five basic contact tracing phases, including case identification, contacts identification and rapid exposure notification, surveillance, regular follow up and prevention. In addition, there is a phase of preparation and post-pandemic services for current and needed future technology that will aid in the fight against any incoming infectious diseases.