The ongoing COVID-19 pandemic let to efforts to develop and deploy digital contact tracing systems to expedite contact tracing and risk notification. Unfortunately, the success of these systems has been limited, partly owing to poor interoperability with manual contact tracing, low adoption rates, and a societally sensitive trade-off between utility and privacy. In this work, we introduce a new privacy-preserving and inclusive system for epidemic risk assessment and notification that aims to address these limitations. Rather than capturing pairwise encounters between user devices as done by existing systems, our system captures encounters between user devices and beacons placed in strategic locations where infection clusters may originate. Epidemiological simulations using an agent-based model demonstrate that, by utilizing location and environmental information and interoperating with manual contact tracing, our system can increase the accuracy of contact tracing actions and may help reduce epidemic spread already at low adoption.

@article{barthe2022listening,
	author = {Barthe, Gilles and Viti, Roberta De and Druschel, Peter and Garg, Deepak and Gomez-Rodriguez, Manuel and Ingo, Pierfrancesco and Kremer, Heiner and Lentz, Matthew and Lorch, Lars and Mehta, Aastha and others},
	journal = {Scientific reports},
	number = {1},
	pages = {1--14},
	publisher = {Nature Publishing Group},
	title = {Listening to Bluetooth beacons for epidemic risk mitigation},
	volume = {12},
	year = {2022}}