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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Yoffe, A., & Ben-Haim, Y. (2006). An info-gap approach to policy selection for bio-terror response. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3975 LNCS, pp. 554–559). Springer Verlag. https://doi.org/10.1007/11760146_56
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