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crc60041

This project evaluated current surveillance systems for EPPs using Bayesian statistical methods and identifed other sources of data that could be used to complement existing surveillance programs. It  also evaluated specific surveillance methods and tests such as visual inspection by field and quality assurance staff and diagnostic tests used in the identification of plant pathogens.

What is the biosecurity problem?

Under the Agreement on the Application of Sanitary and Phytosanitary Measures (SPS agreement) countries are no longer allowed to restrict imports of plant products for non-scientifically justifiable reasons and the need to provide valid data supporting the status of plant pathogens of concern is becoming increasingly important.

Current plant pathogen surveillance systems are often focused on targeted surveillance for a specific pathogen and methods are based on 'expert opinion' and historically used tests. These surveillance systems only report on the pest status in a particular time period, effectively a ‘snapshot' and are often expensive to implement due to the large number of samples required to provide sufficient confidence of obtaining an accurate representation of the pest status in a given region or country at that time.

The main outputs of this project were to:

  • assess the application of statistical and modeling tools for their evaluation of plant health surveillance systems
  • develop methods for identifying different risks in population subgroups based on risk-based analysis
  • develop methods for risk-based surveillance design
  • statistically evaluate methods and tests currently used in surveillance systems, and
  • assess alternative sources of data available that may contribute towards demonstrating disease freedom and early detection of EPPs.

Who are the end-users of this research?

The tools and methodologies developed in this project are most applicable to government departments for use in designing future surveillance programs, assessing current surveillance programs and demonstrating disease freedom for use in the support of market access applications. The tools and methods developed are also applicable for assessing surveillance data supplied by trading partners as part of import applications.

STUDENT


Ms Nichole Hammond
Student CRC60041: Surveillance Systems Analysis - PhD

N.Hammond@murdoch.edu.au
Phone: 08 9360 6124
Fax: (08) 9310 4144

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PROJECT DETAILS

Status
Complete
Supervisor
Dr Darryl Hardie, Department of Agriculture and Food, WA
Supervising Institution
Murdoch University
Term
January 2007 - December 2009

LOCATION