Abstract
Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In this Part I, we provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effect- in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. The companion paper Part II surveys other emerging and related technologies, such as machine learning, computer vision, thermal, ultrasound, etc., and discusses open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice.
Highlights
COVID-19 has completely changed the world’s view on pandemics with dire consequences to global health andThe associate editor coordinating the review of this manuscript and approving it for publication was Derek Abbott .economy
Social distancing has been considered a crucial measure to prevent the spread of contagious diseases such as COVID-19
We have presented a comprehensive survey on how technologies can enable, encourage, and enforce social distancing
Summary
COVID-19 has completely changed the world’s view on pandemics with dire consequences to global health andThe associate editor coordinating the review of this manuscript and approving it for publication was Derek Abbott .economy. To evaluate the effectiveness of social distancing, a common approach is to measure the attack rate which is the percentage of infected people in a susceptible population (where no one is immune at the beginning of the disease) at the time of measurement [27].
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