Contact tracing has been a widely-discussed technique for controlling COVID-19. The traditional test-trace-isolate-support paradigm focuses on identifying people after they have been exposed to positive individuals, and isolating them to protect others. This article introduces an alternative and complementary approach, which appears to be the first to notify people before exposure happens, in the context of their interaction network, so that they can directly take actions to avoid exposure themselves, without using personally identifiable information. Our system has just become achievable with present technology: for each positive case, do not only notify their direct contacts, but inform thousands of people of how far away they are from the positive case, as measured in network-theoretic distance in their physical relationship network. This fundamentally different approach has already been deployed in a publicly downloadable app. It brings a new tool to bear on the pandemic, powered by network theory. Like a weather satellite providing early warning of incoming hurricanes, it empowers individuals to see transmission approaching from far away, and to directly avoid exposure in the first place. This flipped perspective engages natural self-interested instincts of self-preservation, reducing reliance on altruism. Consequently, our new system could solve the behavior coordination problem which has hampered many other app-based interventions to date. We also provide a heuristic mathematical analysis that shows how our system already achieves critical mass from the user perspective at very low adoption thresholds (likely below 10% in some common types of communities as indicated empirically in the first practical deployment); after that point, the design of our system naturally accelerates further adoption, while also alerting even non-users of the app.
Flipping the Perspective in Contact Tracing