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When we speak of the next pandemic, it's no longer a question of "if" but "when". The NSF research community is uniquely placed to ensure that multidisciplinary and cutting-edge science is applied to real-time real-world situations. Join us as we talk to the scientists at the heart of these innovations - and through our special "researcher match" episodes, we hope to spark new ideas and collaborations among researchers. This is Science before the Storm. |
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The COVID-19 pandemic has emphasized the need for a more robust disease surveillance infrastructure. However, the development of such an infrastructure runs into a double-bind. Assurances of privacy require adversarial testing against realistic systems. Likewise, it is difficult to build realistic systems without access to data. To get around this problem, we created synthetic datasets that reflect a realistic disease outbreak. This data was used as a component in the US-UK Prize Challenge on Privacy-Enhancing Technologies. In the challenge, participants were tasked with creating personalized risk forecasts of infection in a privacy-preserving manner. The challenge was put on by the U.K.’s Center for Data Ethics and Innovation (CDEI) and Innovate UK, as well as by the U.S. National Institutes of Standards and Technology (NIST), and the National Science Foundation (NSF) in cooperation with the White House Office of Science and Technology Policy (OSTP). The winners of the US and UK challenges were announced on March 30, at the Summit for Democracy. The winning teams can be found here, and profiles of the teams can be found here.
Over two years since the PREPARE virtual organization was created, we’ve synthesized a research roadmap based on what we’ve learned from workshops we’ve hosted, conversations with community members, podcast interviews, and literature review. And we’re coming together to get some final input from the community—did we get it right? what are we missing? what are general lessons learned you’d like to share with the NSF? Go to our Roadmap Forum to leave your comments. We’d also like to give people an opportunity to keep the discussion going and share any recent work at the RP3: Research for Pandemic Preparedness workshop! Register here!
To tackle financial crime and public health emergencies, the UK-US Privacy-Enhancing Technology challenge is using synthetic datasets created by UVA’s Network Systems Science and Advanced Computing (NSSAC) Division!
The challenge is focused on accelerating the adoption and development of privacy-enhancing technologies (PETs). In particular, the two challenges focus on using privacy-preserving federated learning to transform financial crime prevention and boost pandemic response capabilities. The NSSAC team at UVA's Biocomplexity Institute has generated the two synthetic population datasets provided in the pandemic response challenge.
Registration Closes: September 2022