RAPID: Collaborative: PPSRC: Privacy-Preserving Self-Reporting for COVID-19

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With the reopening of the country and the restarting of economic as well as other activities, it becomes important to ensure vigilantly monitoring the spreading of COVID-19 and nimbly adjusting the policies accordingly. Technologies can play an important role in this process. This project aims at understanding how mobile-app based contact tracing and symptom monitoring technologies can help in fighting COVID-19 and deploying effective technologies. It is expected that knowledge learned through the project can be a valuable tool to fight SARS-CoV-2 as well as future emerging pathogens. This project has two thrusts. Thrust 1 studies to what extent contact tracing based on mobile phones can help. Thrust 1 has three tasks. First, summarize the design choices of existing proposals, systematically explore the design space, and identify potential privacy and security attacks and possible defenses. Second, use existing data related to contact tracing to understand the epidemiological characteristics of COVID-19. Third, assess the effectiveness of technology-aided case finding and contact-tracing using simulation models. Thrust 2 aims at developing Privacy-Preserving COVID-19 Symptom Monitoring Technologies, through three tasks. First, design and implement privacy protection technologies based on local differential privacy. Second, design and implement an App for self-reporting of symptoms. Third, integrate data collected from the app with data from other public sources, and model the integrated data using a dynamic state-space model to provide early warning for high risk districts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.