DHS announces finalists for $300K challenge to develop emerging biothreat detection system

The Department of Homeland Security (DHS) Science & Technology Directorate (S&T) named five finalists for a $300,000 grant to develop an early warning system that detects emerging biothreats using existing data on Wednesday.

Finalists for the grant, which is being administered by the S&T Directorate and the Office of Health Affairs National Biosurveillance Integration Center (NBIC), were announced at the American Society for Microbiology’s 2018 ASM Biothreats meeting.

“We were impressed with the diversity of concepts submitted to the challenge,” William Bryan, the senior DHS official performing the duties of under secretary for science and technology, said. “The five finalists explore new ways we can uncover emerging biothreats and we are confident they’ll inform a system that could enable city-level operators to make critical decisions.”

Readiness Acceleration & Innovation Network (RAIN), based in Tacoma, Washington, was named a finalist for a tool that uses existing municipal health data, internet keyword searches and de-identified traffic information to detect absenteeism in the early stages of an outbreak.

Vituity of Emeryville, California, was named a finalist for a model that alerts authorities when emergency room wait times spike using real-time data from 142 hospitals in 19 states.

William Pilkington and his team in Cabarrus County, North Carolina, were named finalists for a system that uses the top symptoms that 43 healthcare providers report in a database and textual predictive analytics to identify potential outbreaks.

Computational Epidemiology Lab at Boston Children’s Hospital was named a finalist for a tool that would use six data streams, social media and Flu Near You transportation data to detect bio-threats.

Daniel Neill and Mallory Nobles of Pittsburgh, Pennsylvania, were named as finalists for a machine learning system that would real-time emergency room data, social media streams and text analysis of news data to detect clusters of rare emerging diseases.

A panel of judges with backgrounds in bioinformatics, biological defense, epidemiology and emergency management selected the finalist. Each will receive $20,000 and advance to the next stage, with the winner being awarded $200,000.