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Strategies for Effective Improvements to the BioWatch System Proceedings of a Workshop (2018) / Chapter Skim
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Appendix G: Invited Paper: Use of Dispersion Modeling Tools in Optimizing Biological Detection Architectures
Pages 144-154

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From page 144...
... Prepared by David F Brown Argonne National Laboratory 144
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From page 145...
... . In the past several years the National Laboratory team has developed the ability to evaluate crossdomain dispersion so that the efficacy of an overall citywide network involving outdoor, subway, and facility detection assets can be assessed (e.g., subway to outdoor, outdoor facility, etc.)
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From page 146...
... 146 FIGURE G-1 Notional example of a subway-to-outdoor release for a fictional subway system.
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From page 147...
... This library is the key part of the analysis as it is interrogated in a Monte Carlo analysis to assess both the biodetector performance and the detection architecture optimization. After constructing the scenario library, differing numbers of detectors with specified performance characteristics are modeled in the appropriate domain, and population exposure models are used to calculate the fraction of population "protected" (Fp)
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From page 148...
... 148 FIGURE G-2 General overiew of detection performance analysis strategy.
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From page 149...
... Other common approaches to the design and optimization of detection system deployments involve designing the system to detect scenarios that involve a particular release mass of biological agent or focus on maximizing the probability of detecting all releases in a given scenario library. The use of these other metrics for system design may be appropriate for designing and evaluating individual detector performance, but they are generally not useful for optimizing op
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From page 150...
... SOURCE: Figure courtesy of Michael Brown, Los Alamos National Laboratory.
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From page 151...
... , green shading denotes that the release originating in that specific grid was detected by the postulated detection architecture. The nonshaded grid locations denote that a release originating from that location was not detected by the postulated architecture.
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From page 152...
... Thresholds Thresholds  Directly related  Straightforward to  Caps upper limit of  Ignores releases to ultimate interest communicate to release size that have little of the BioWatch key stakeholders according to threat impact on program (i.e.,  Analysis is likelihoods population Advantage detecting releases independent of  Directly related to  Straightforward to that infect large dose-response ultimate interest of communicate number of people) behavior for an the BioWatch  De-emphasizes agent program releases that have  De-emphasizes little impact releases that have little impact  Metric requires  Population impacts  Some knowledge  Results sensitive more effect to are not included so of release size to threshold communicate than all scenarios are threat likelihood is infection cutoff other metrics considered equally required value selected and  Results can be important to detect  Metric requires can be useless in driven by scenarios  Sensitive to more effort to assessing the Disadvantages with large release parameter ranges communicate than marginal benefit sizes (which may be that bound other metrics of additional unlikely to occur)
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From page 153...
... constant deployment size. SOURCE: Figure courtesy of Sandia National Laboratory.
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From page 154...
... Subway Tracer Transport and Dispersion Experiments: Meas urements and Analysis. Argonne National Laboratory, FOUO Technical Report ANL/DIS-09-03.
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Key Terms

  • scenario library
  • release size
  • performance metrics
  • detector performance
  • overall performance

  • detection architecture
  • key modeling
  • biowatch program
  • subway tracer
  • population protected

  • design metric
  • argonne national
  • stakeholder community
  • analysis strategy
  • related studies

  • figure courtesy
  • example comparing
  • outdoor releases
  • single scenario
  • illustrative example

  • biological agent
  • marginal benefit
  • particle size
  • release originating
  • assess overall

  • design metrics
  • release sizes
  • meteorological condition
  • monte carlo
  • detection performance


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