A Survey of COVID-19 Contact Tracing Apps

TLDR

The COVID‑19 pandemic, characterized by high infectivity and asymptomatic transmission, has strained health systems and prompted governments to consider smartphone contact‑tracing apps. This review surveys the key attributes of contact‑tracing apps and outlines future research directions for improved design and adoption. The authors compile examples of existing apps, discuss their architectures, data handling, privacy, security, proximity estimation, and user concerns, and evaluate their deployment status.

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.