The role of data warehousing in bioterrorism surveillance

Authors:
Donald J. Berndt;John W. Fisher;Jamie Griffiths Craighead;Alan R. Hevner;Stephen Luther;James Studnicki
Affiliations:
Information Systems and Decision Sciences, College of Business Administration, University of South Florida, Tampa, FL 33620, United States;Information Systems and Decision Sciences, College of Business Administration, University of South Florida, Tampa, FL 33620, United States;Information Systems and Decision Sciences, College of Business Administration, University of South Florida, Tampa, FL 33620, United States;Information Systems and Decision Sciences, College of Business Administration, University of South Florida, Tampa, FL 33620, United States;College of Public Health, University of South Florida, Tampa, FL 33620, United States;College of Public Health, University of South Florida, Tampa, FL 33620, United States
Venue:
Decision Support Systems
Year:
2007

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Abstract

The development of an effective bioterrorism surveillance system requires effective solutions to several critical challenges. The system must support multidimensional historical data, provide real-time surveillance of sensor data, have the capability for pattern recognition to quickly identify abnormal situations, and provide an analytic environment that accelerates investigations by epidemiologists and other responders. The use of real-time or flash data warehousing provides the essential ability to compare unfolding health events with historical patterns of key surveillance indicators. To explore the role of data warehousing in surveillance systems, we study naturally occurring incidents, Florida wildfires from 1996 through 2001, as reasonable facsimiles of bioterrorism attacks. Hospital admissions data on respiratory illnesses during that period are analyzed to uncover patterns that might resemble an airborne biochemical attack. A principal contribution of this research is the adroit use of online analytic processing (OLAP) techniques, along with spatial and statistical analyses, to study the adverse effects of this natural phenomenon. These techniques will provide important capabilities for epidemiologist-in-the-loop surveillance systems, enabling the rapid exploration of unusual situations and guidance for follow-up investigations.