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Simulation for assessing statistical methods of biologic terrorism surveillance.
Ken P Kleinman1, A Abrams, K Mandl
1Harvard Medical School, Harvard Pilgrim Health Care, and CDC Eastern Massachusetts Prevention Epicenter and HMO Research Network Center for Education and Research in Therapeutics, Boston, Massachusetts 02215, USA. ken_kleinman@harvardpilgrim.org
MMWR Supplements
|September 24, 2005
Summary
Simulation of anthrax spore dispersal demonstrates that combining surveillance data streams significantly improves early warning detection. This approach is superior to using individual data streams for public health surveillance.
Area of Science:
- Public Health
- Epidemiology
- Biosecurity
Background:
- Developing effective early warning systems for bioterrorism is crucial.
- Limited practical data exists for evaluating alarm-generating algorithms in syndromic surveillance.
- Simulation offers a viable method for assessing algorithm performance.
Purpose of the Study:
- To describe a simulation model for anthrax spore dispersal.
- To evaluate the performance of different statistical algorithms for syndromic surveillance.
- To compare the effectiveness of single versus combined data streams.
Main Methods:
- A simulation of anthrax spore dispersal from an aircraft was developed.
- Simulated cases were integrated into a data stream for analysis.
- Detection methods included SaTScan and small area regression and testing (SMART) scores.
- An evaluation metric was created to compare algorithm performance.
Main Results:
- Two statistical approaches showed similar performance in a single data stream simulation.
- Combined surveillance data from two streams proved superior to individual streams.
- The simulation highlighted the benefits of integrating diverse data sources.
Conclusions:
- Simulation is a valuable tool for evaluating and planning syndromic surveillance systems.
- This method can compare different data sources and assess system modifications.
- Simulation aids in optimizing public health surveillance strategies for bioterror threats.
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