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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 15 (Page no: 265)

Evidence of absence for invasive species: roles for hierarchical Bayesian approaches in regulation.

Regulatory agencies responsible for managing pest incursions rely upon an adequate knowledge of the distribution of the pest. Spatio-temporal estimates of distribution for an actively invading pest require ecological and surveillance information to be assimilated, a task which is well suited to hierarchical Bayesian inference. The process of developing a pest observation model and a pest status model to evaluate the evidence for absence is explained in relation to existing simple models used for biosecurity surveillance. A case study to estimate the probability of exotic fruit fly absence in a district illustrates how simple invasion process models can be incorporated into the analysis of surveillance programmes. Trapping information from a previous incursion of Bactrocera papayae in Queensland in 1995 is brought into the detection model. The economic value of maintaining or altering the surveillance programme is assessed in terms of the putative costs of incursion management given different surveillance regimes.

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: 8 (Page no: 151) Estimating detection rates and probabilities. Author(s): Hauser, C. E. Garrard, G. E. Moore, J. L.
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: 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 Mathematical Sciences, Queensland University of Technology, Gardens Point Campus, PO Box 2434, Brisbane, Queensland 4001, Australia.
  • Year of Publication
  • 2015
  • ISBN
  • 9781780643595
  • Record Number
  • 20153099603