Robustness of surveillance for biosecurity with detection uncertainty

Surveillance for invasive non-indigenous species (NIS) is an integral part of a quarantine system. Estimating the efficiency of a surveillance strategy relies on many uncertain parameters estimated by experts, such as the efficiency of its components in face of the specific NIS, the ability of the N...

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Main Authors: Majer, Jonathan, Davidovitch, L., Stoklosa, R.
Format: Journal Article
Published: 2009
Online Access:http://hdl.handle.net/20.500.11937/13530
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author Majer, Jonathan
Davidovitch, L.
Stoklosa, R.
author_facet Majer, Jonathan
Davidovitch, L.
Stoklosa, R.
author_sort Majer, Jonathan
building Curtin Institutional Repository
collection Online Access
description Surveillance for invasive non-indigenous species (NIS) is an integral part of a quarantine system. Estimating the efficiency of a surveillance strategy relies on many uncertain parameters estimated by experts, such as the efficiency of its components in face of the specific NIS, the ability of the NIS to inhabit different environments, and so on. Due to the importance of detecting an invasive NIS within a critical period of time, it is crucial that these uncertainties be accounted for in the design of the surveillance system. We formulate a detection model that takes into account, in addition to structured sampling for incursive NIS, incidental detection by untrained workers. We use info-gap theory for satisficing (not minimizing) the probability of detection, while at the same time maximizing the robustness to uncertainty. We demonstrate the trade-off between robustness to uncertainty, and an increase in the required probability of detection. An empirical example based on the detection of Pheidole megacephala on Barrow Island demonstrates the use of info-gap analysis to select a surveillance strategy.
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spelling curtin-20.500.11937-135302019-05-17T01:53:33Z Robustness of surveillance for biosecurity with detection uncertainty Majer, Jonathan Davidovitch, L. Stoklosa, R. Surveillance for invasive non-indigenous species (NIS) is an integral part of a quarantine system. Estimating the efficiency of a surveillance strategy relies on many uncertain parameters estimated by experts, such as the efficiency of its components in face of the specific NIS, the ability of the NIS to inhabit different environments, and so on. Due to the importance of detecting an invasive NIS within a critical period of time, it is crucial that these uncertainties be accounted for in the design of the surveillance system. We formulate a detection model that takes into account, in addition to structured sampling for incursive NIS, incidental detection by untrained workers. We use info-gap theory for satisficing (not minimizing) the probability of detection, while at the same time maximizing the robustness to uncertainty. We demonstrate the trade-off between robustness to uncertainty, and an increase in the required probability of detection. An empirical example based on the detection of Pheidole megacephala on Barrow Island demonstrates the use of info-gap analysis to select a surveillance strategy. 2009 Journal Article http://hdl.handle.net/20.500.11937/13530 10.1016/j.jenvman.2009.03.011 restricted
spellingShingle Majer, Jonathan
Davidovitch, L.
Stoklosa, R.
Robustness of surveillance for biosecurity with detection uncertainty
title Robustness of surveillance for biosecurity with detection uncertainty
title_full Robustness of surveillance for biosecurity with detection uncertainty
title_fullStr Robustness of surveillance for biosecurity with detection uncertainty
title_full_unstemmed Robustness of surveillance for biosecurity with detection uncertainty
title_short Robustness of surveillance for biosecurity with detection uncertainty
title_sort robustness of surveillance for biosecurity with detection uncertainty
url http://hdl.handle.net/20.500.11937/13530