Abstract/Details

Predicting biological warfare agent detector performance


2008 2008

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Abstract (summary)

Biological warfare agents (BWAs) are inherently dangerous. United States of America public law forbids the release of biological warfare agent into the environment. The test and evaluation community desires realistic open air field tests, but does not want to risk harming test participants or the general public. Neither do they want to break the law by releasing actual BWAs during open air field tests.

To test biological defense systems in the field, the test and evaluation community releases relatively harmless substances known as simulants. It is highly desirable that the biological warfare system under test performs identically with the simulant as it does with real biological warfare agent. Unfortunately this never occurs.

A new class of simulants known as Agent-Like Organism (ALO) has been developed. An ALO is phylogenetically closely related to its corresponding biological warfare agent. A vaccine strain is an example of ALO.

The purpose of this dissertation is twofold: to determine if killed or inactivated ALOs are acceptable simulants for a biological point detection system that uses particle fluorescence and immunoassay technology; and to develop a model based on logistic regression to relate detector simulant performance to detector performance with biological warfare agent.

Data for this analysis was obtained from Dugway Proving Ground, Utah. The data set consisted of 2,717 Joint Biological Point Detector System (JBPDS) challenges. The system was challenged with either BWA or ALO simulant. All BWA challenges occurred in a Bio-Level 3 (BL-3) facility. Data was analyzed using logistic regression. The determination as to the acceptability of the ALOs as simulants was based on both statistical analysis and judgment on the impact of differences on the performance in an open air field test.

Results are given that show the acceptability of various simulants for particular BWAs with respect to both detection and identification. The simple models examined in this dissertation do not adequately explain the variability that occurs in field open air releases. As a result of unexplained variability in detector performance during open air field releases, even the best predictive model is of minimal utility in predicting detector performance.

The best predictor of biological warfare agent detector performance is field trials with killed ALOs. A possible method to improve the acceptability of Killed N ALO and Killed NU ALO as identification simulants is discussed.

Indexing (details)


Subject
Microbiology;
Operations research
Classification
0410: Microbiology
0796: Operations research
Identifier / keyword
Applied sciences; Biological sciences; ALO; Agent-like organisms; Biodefense; Biological warfare agents; Detector; Model; Test
Title
Predicting biological warfare agent detector performance
Author
Holman, Charles E.
Number of pages
245
Publication year
2008
Degree date
2008
School code
0883
Source
DAI-B 69/05, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9780549639176
Advisor
Loerch, Andrew
University/institution
George Mason University
University location
United States -- Virginia
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3313514
ProQuest document ID
230866122
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/230866122
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