Systems Modeling for Rapid Containment and Casualty Mitigation

• Activity Number: 293
• Type: Invited
• Date/Time: Tuesday, August 11, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Section on Risk Analysis
• Author(s): Eva Lee*
• Companies: Georgia Institute of Technology

Abstract

Computational modeling and technology that facilitate rapid detection of infected individuals, containment strategy development, tradeoff analysis, optimal resource allocation, and look-ahead vision of results are of paramount importance for combating bioterrorism and infectious disease outbreaks. Such capabilities are fundamental to the public health emergency response infrastructure, and are critical to our national public health population protection mission. In this talk, we describe a computational decision support framework that optimizes scarce resources for rapid disease containment. Our approach will couple a disease propagation model with both a dispensing/treatment queuing model and optimization engine to determine the optimal resources needed for disease containment. The resulting system will empower on-the-ground policy makers with strategies for effective casualty mitigation, risk monitoring and tracing, and population protection during a biological event, under strained time and limited medical/labor supplies. The system has real-time capability for live data-feeds and allows re-configuration on the fly as the event unfolds. This work is joint with CDC.