DHS S&T has announced the grand prize winner of its $300,000 Hidden Signals Challenge.
The prize competition, issued in collaboration with the Office of Health Affairs National Biosurveillance Integration Center (NBIC), called for the design of an early warning system to keep communities safe by using existing data sources to uncover emerging biothreats.
The Computational Epidemiology Lab at Boston Children’s Hospital will receive the grand prize of $150,000 for their proposed solution called Pandemic Pulse. 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.
“By exploring these untapped data sources we aim to improve how city-level operators make important public safety decisions,” said William N. Bryan, DHS Senior Official Performing the Duties of Under Secretary for Science and Technology. “The grand prize winner and runner-up have strong system designs that harness streams of information in a manner that could allow us to identify an emerging problem faster.”
The runner-up solution, Pre-syndromic Surveillance, submitted by Daniel B. Neill and Mallory Nobles of Pittsburgh, Pa., will receive $50,000. 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.
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 for Stage 2 of the Challenge. In Stage 1, five finalists received $20,000 each and refined their submissions during the Virtual Accelerator.
“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,” said Dr. John Brownstein, director of the Computational Epidemiology Lab at Boston Children’s Hospital. “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.”
For more information about the Hidden Signals Challenge, visit hiddensignalschallenge.com.
