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An Info-Gap Approach to Policy Selection for Bio-terror Response

  • Anna Yoffe
  • Yakov Ben-Haim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3975)

Abstract

Bio-terror events are accompanied by severe uncertainty: great disparity between the best available data and models, and the actual course of events. We model this uncertainty with non-probabilistic information-gap models of uncertainty. This paper focuses on info-gaps in epidemiological models, in particular, info-gaps in the rate of infection. robustness to uncertainty is defined as a function of the required critical morbidity resulting from the attack. We show how preferences among available interventions are deduced from the robustness function. We demonstrate the irrevocable trade-off between robustness and demanded performance, and show that best-estimated performance has zero robustness. Finally, we present a theorem concerning the reversal of preferences between available interventions, and illustrate it with a numerical example.

Keywords

Infection Volume Epidemiological Model Policy Selection Robustness Function Critical Infection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Anna Yoffe
    • 1
  • Yakov Ben-Haim
    • 2
  1. 1.Faculty of Mechanical EngineeringTechnionHaifaIsrael
  2. 2.Yitzhak Moda’i Chair in Technology and Economics, Faculty of Mechanical EngineeringTechnionHaifaIsrael

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