Lessons Learned in Piloting a Digital Personalized COVID-19 "Radar" on a University Campus.

Health authorities encouraged the use of digital contact tracing mobile applications (apps) during the COVID-19 pandemic, but the level of adoption was low because apps offered few direct benefits to counterbalance risks to personal privacy. Adoption of such apps could improve if they provided benefits to users. NOVID (COVID-19 Radar), a smartphone app, provided users with personalized data on social proximity of COVID-19 cases and exposed contacts. We analyzed uptake of NOVID at the Georgia Institute of Technology (Georgia Tech) during the 2020-2021 academic year. Data included anonymous NOVID users who self-identified with Georgia Tech and their first- and second-degree network contacts. NOVID achieved 13%-30% adoption at Georgia Tech. Because of technical challenges, adoption waned after an initial peak. The largest increases in adoption (from 41 to 3704) followed administrative promotion of NOVID. Adoption increased modestly (from 2512 to 2661) after faculty- and student-led promotion, such as distribution of door hangers and a public seminar. Two-thirds of on-campus NOVID users were connected to a large network of other users, enabling them to receive data on social proximity of COVID-19 cases and exposed contacts. Network cohesion was observed to emerge rapidly when adoption rates passed just 10%, consistent with estimates from network theory. The key lesson learned in this case study is that top-down administrative promotion outperforms bottom-up grassroots promotion. Relatively high levels of adoption and network cohesion, despite technical challenges during the Georgia Tech pilot of NOVID, illustrate the promise of digital contact tracing when apps provide privacy and inherently beneficial personalized data to their users, especially in regions where Google Apple Exposure Notification is not available.

Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World.

As COVID-19 hounds the world, the common cause of finding a swift solution to manage the pandemic has brought together researchers, institutions, governments, and society at large. The Internet of Things (IoT), artificial intelligence (AI)-including machine learning (ML) and Big Data analytics-as well as Robotics and Blockchain, are the four decisive areas of technological innovation that have been ingenuity harnessed to fight this pandemic and future ones. While these highly interrelated smart and connected health technologies cannot resolve the pandemic overnight and may not be the only answer to the crisis, they can provide greater insight into the disease and support frontline efforts to prevent and control the pandemic. This article provides a blend of discussions on the contribution of these digital technologies, propose several complementary and multidisciplinary techniques to combat COVID-19, offer opportunities for more holistic studies, and accelerate knowledge acquisition and scientific discoveries in pandemic research. First, four areas, where IoT can contribute are discussed, namely: 1) tracking and tracing; 2) remote patient monitoring (RPM) by wearable IoT (WIoT); 3) personal digital twins (PDTs); and 4) real-life use case: ICT/IoT solution in South Korea. Second, the role and novel applications of AI are explained, namely: 1) diagnosis and prognosis; 2) risk prediction; 3) vaccine and drug development; 4) research data set; 5) early warnings and alerts; 6) social control and fake news detection; and 7) communication and chatbot. Third, the main uses of robotics and drone technology are analyzed, including: 1) crowd surveillance; 2) public announcements; 3) screening and diagnosis; and 4) essential supply delivery. Finally, we discuss how distributed ledger technologies (DLTs), of which blockchain is a common example, can be combined with other technologies for tackling COVID-19.