A Survey of COVID-19 Contact Tracing Apps

Abstract

The recent outbreak of COVID-19 has taken the world by surprise, forcing lockdowns and straining public health care systems. COVID-19 is known to be a highly infectious virus, and infected individuals do not initially exhibit symptoms, while some remain asymptomatic. Thus, a non-negligible fraction of the population can, at any given time, be a hidden source of transmissions. In response, many governments have shown great interest in smartphone contact tracing apps that help automate the difficult task of tracing all recent contacts of newly identified infected individuals. However, tracing apps have generated much discussion around their key attributes, including system architecture, data management, privacy, security, proximity estimation, and attack vulnerability. In this article, we provide the first comprehensive review of these much-discussed tracing app attributes. We also present an overview of many proposed tracing app examples, some of which have been deployed countrywide, and discuss the concerns users have reported regarding their usage. We close by outlining potential research directions for next-generation app design, which would facilitate improved tracing and security performance, as well as wide adoption by the population at large.

IEF2C: A novel AI-powered framework for suspected COVID-19 patient detection and contact tracing in smart cities

“…An epidemic model has been designed to evaluate the efficient contact tracing app and those communication technologies have been applied for simulation purposes [39]. The contact tracing app has some attributes such as data management, system architecture, privacy, proximity, security estimation and vulnerability [40]. To make the contact tracing system successful, COVID-19 testing should be increased.…”

Blockchain and COVID-19 Pandemic: Applications and Challenges

“…For example, many corporate sectors such as Google and Apple have recently launched contact tracing applications that can help authorities to trace COVID-19 infected persons. But, the existing solutions have to access personal data such as location and COVID-19 test results of an individual to identify the spread rate and predict viral hotspots within a community [7][8][9]. A large portion of the proposed systems has followed centralized architecture to access, store services, and data related to COVID-19.…”

“…A large portion of the proposed systems has followed centralized architecture to access, store services, and data related to COVID-19. For instance, Singapore's contact tracing solution called TraceTogether, employs Bluetooth technology to discover the close contact of a person with an infected patient with COVID-19 [8,10,11]. Being a centralized governed solution, the contact tracing service providers can access user data to compromise data privacy.…”

“…In [23], researchers studied the possible benefits of integrating AI with blockchain technology to minimize the spreading of COVID-19. Nadeem et al [8] surveyed existing digital contact tracing schemes to combat the COVID-19 pandemic. Unlike the aforementioned surveys, our work is comprehensively focused on health emergency services.…”

Spatiotemporal event sequence discovery without thresholds

“…Public health researchers, particularly epidemiologists, can also benefit from STES mining for understanding the frequently occurring activities leading to spread of infectious diseases. Contact tracing applications [ 1 ] are one of the very few tools we can deploy to stop the spread of viral diseases with great epidemic potential such as the novel coronavirus (SARS-CoV-2) [ 19 ]. Such applications can be used to trace the movements of individuals and the paths of individuals can be split into activity event types.…”