When animals are transported and pass through customs, some of them may have dangerous infectious diseases. Typically, due to the cost of testing, not all animals are tested: a reasonable selection must be made. How to test effectively, yet avoid cataclysmic events? First, we extend a model proposed in the literature for the detection of invasive species to suit our purpose. Secondly, we explore and compare two decision methodologies on the problem at hand, namely, info-gap theory and imprecise probability theory, both of which are designed to handle severe uncertainty. We show that, under rather general conditions, every info-gap solution is maximal with respect to a suitably chosen imprecise probability model, and that therefore, perhaps surprisingly, the set of maximal options can be inferred at least partly---and sometimes entirely---from an info-gap analysis.
The paper is available in the following formats:
Plenary talk: file
Poster: file
Matthias Troffaes
Department of Mathematical Sciences
Durham University
Science Laboratories, South Road
Durham, DH1 3LE
John Paul Gosling
The Food and Environment Research Agency
Sand Hutton
York YO41 1LZ
| Matthias Troffaes | matthias.troffaes@gmail.com | |
| John Paul Gosling | johnpaul.gosling@fera.gsi.gov.uk |
Send any remarks to isipta11@uibk.ac.at.