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CABI Book Chapter

Biosecurity surveillance: quantitative approaches.

Book cover for Biosecurity surveillance: quantitative approaches.

Description

Biosecurity surveillance plays a vital role in protection against the introduction and spread of unwanted plants and animals. It involves not just collecting relevant information, but also analysing this information. This book focuses on methods for quantitative analysis of biosecurity surveillance data, where these data might arise from observations, sensors, remote imaging, expert opinion and so...

Chapter 8 (Page no: 151)

Estimating detection rates and probabilities.

Surveillance activities provide only imperfect detection of biosecurity threats, and so quantifying detection rates and probabilities is important for making reliable inferences from survey data. Furthermore, an understanding of detection rates and probabilities allows for effective survey design and resource allocation to address biosecurity threats. Detection rates and probabilities can be estimated directly via experiments or indirectly during routine surveillance activities. In this chapter we introduce basic presence/absence detection models and provide guidelines for designing a detection experiment. We also summarize other methods available for estimating detection rates and probabilities when pest abundance, as well as presence/absence, affects management.

Other chapters from this book

Chapter: 1 (Page no: 1) Introduction to Biosecurity surveillance: quantitative approaches. Author(s): Jarrad, F.
Chapter: 2 (Page no: 9) Biosecurity surveillance in agriculture and environment: a review. Author(s): Quinlan, M. Stanaway, M. Mengersen, K.
Chapter: 3 (Page no: 43) Getting the story straight: laying the foundations for statistical evaluation of the performance of surveillance. Author(s): Low-Choy, S.
Chapter: 4 (Page no: 75) Hierarchical models for evaluating surveillance strategies: diversity within a common modular structure. Author(s): Low-Choy, S.
Chapter: 5 (Page no: 109) The relationship between biosecurity surveillance and risk analysis. Author(s): MacLeod, A.
Chapter: 6 (Page no: 123) Designing surveillance for emergency response. Author(s): Havre, Z. van Whittle, P.
Chapter: 7 (Page no: 137) The role of surveillance in evaluating and comparing international quarantine systems. Author(s): Mittinty, M. Whittle, P. Burgman, M. Mengersen, K.
Chapter: 9 (Page no: 167) Ad hoc solutions to estimating pathway non-compliance rates using imperfect and incomplete information. Author(s): Robinson, A. P. Chisholm, M. Mudford, R. Maillardet, R.
Chapter: 10 (Page no: 181) Surveillance for soilborne microbial biocontrol agents and plant pathogens. Author(s): Whittle, P. Sundh, I. Neate, S.
Chapter: 11 (Page no: 203) Design of a surveillance system for non-indigenous species on Barrow Island: plants case study. Author(s): Murray, J. Whittle, P. Jarrad, F. Barrett, S. Stoklosa, R. Mengersen, K.
Chapter: 12 (Page no: 217) Towards reliable mapping of biosecurity risk: incorporating uncertainty and decision makers' risk aversion. Author(s): Yemshanov, D. Koch, F. H. Ducey, M. Haack, R. A.
Chapter: 13 (Page no: 238) Detection survey design for decision making during biosecurity incursions. Author(s): Kean, J. M. Burnip, G. M. Pathan, A.
Chapter: 14 (Page no: 253) Inference and prediction with individual-based stochastic models of epidemics. Author(s): Gibson, G. Gilligan, C. A.
Chapter: 15 (Page no: 265) Evidence of absence for invasive species: roles for hierarchical Bayesian approaches in regulation. Author(s): Stanaway, M.
Chapter: 16 (Page no: 278) Using Bayesian networks to model surveillance in complex plant and animal health systems. Author(s): Johnson, S. Mengersen, K. Ormsby, M. Whittle, P.
Chapter: 17 (Page no: 296) Statistical emulators of simulation models to inform surveillance and response to new biological invasions. Author(s): Renton, M. Savage, D.
Chapter: 18 (Page no: 313) Animal, vegetable, or ...? A case study in using animal-health monitoring design tools to solve a plant-health surveillance problem. Author(s): Hester, S. Sergeant, E. Robinson, A. P. Schult, G.
Chapter: 19 (Page no: 334) Agent-based Bayesian spread model applied to red imported fire ants in Brisbane. Author(s): Keith, J. M. Spring, D.

Chapter details

  • Author Affiliation
  • School of Botany, The University of Melbourne, Parkville, Victoria 3010, Australia.
  • Year of Publication
  • 2015
  • ISBN
  • 9781780643595
  • Record Number
  • 20153099596