Announcing the Challenge winners
Today DHS announced the grand prize winner and runner-up of the Hidden Signals Challenge! Congratulations to the grand prize winner Pandemic Pulse from the Computational Epidemiology Lab at Boston Children’s Hospital, and runner-up Pre-syndromic Surveillance by Daniel B. Neill and Mallory Nobles.
These two system designs employ publicly available data sources to help identify an emerging biothreat faster. Pandemic Pulse won $150,000 and Pre-syndromic Surveillance won $50,000 as rewards for their noteworthy progress towards deployable systems.
The grand prize-winning system design:
Pandemic Pulse (Computational Epidemiology Lab at Boston Children’s Hospital): This system provides a dashboard that integrates Twitter and Google Search data with infectious disease monitoring tools, Flu Near You and HealthMap, to detect biothreat signals. The tool filters data based on pathogen category, information source, and transmission mode, using a tiered evaluation method.
“The Pandemic Pulse system utilizes digital exhaust of syndromic data to detect and monitor biothreats. The signals from various informal monitoring sources will be utilized in a sensitivity-driven layered approach for detecting and presenting signals from well-known, to less-familiar biothreats. Participating in the Hidden Signals Challenge was extremely exciting and interesting. Mentorship from some of the best in the field and access to informative online resources made our participation extremely rewarding and efficacious.”
– John Brownstein, Director of the Computational Epidemiology Lab at Boston Children’s Hospital
The runner-up system design:
Pre-syndromic Surveillance (Daniel B. Neill and Mallory Nobles): This system integrates emergency department chief complaints with data from health clinics and social media to discover outbreaks that do not correspond with known illnesses. The team is piloting a working prototype with New York City’s Department of Health and Mental Hygiene and other city agencies.
“We believe that it is critical for public health practitioners to have a ‘safety net’ which can identify and investigate newly emerging outbreaks and previously unseen biothreats that existing systems are unable to detect. Our pre-syndromic surveillance system will facilitate a targeted, coordinated, and effective response to emerging health threats.”
– Daniel B. Neill, Director, Event and Pattern Detection Laboratory, Heinz College of Information Systems and Public Policy, Carnegie Mellon University. From July 1st : Associate Professor of Computer Science, Public Service, and Urban Analytics, New York University
A panel of seven judges with expertise in bioinformatics, biological defense, epidemiology, and emergency management helped to select the grand prize winner and runner-up. This announcement concludes Stage 2 of the Challenge. Stage 1 awarded $100,000 to five finalists, who each received $20,000 and refined their submissions during the Virtual Accelerator.
We congratulate all of the Challenge prize-winners and wish them luck as they continue to develop their solutions.