Presented by: Simone Tuten on behalf of the Department of Agriculture, Western Australia Plant Biosecurity Team. International Plant Health Risk Analysis Workshop Niagara Falls, October 2005 A new semi-quantitative model to determine pest introduction frequency

Please note: The research reported here is in progress and is not finalised. The study results have not been subjected to scientific peer review and are presented purely as a demonstration of the authors’ current thinking. This presentation reflects the authors’ opinions and does not necessarily reflect the opinions of the Department of Agriculture, Western Australia. Additionally this research has been undertaken by the Western Australian State Department of Agriculture and not by National Government Departments. Any reliance on the information presented here is entirely at your own risk and the Department of Agriculture, Western Australia takes no responsibility whatsoever for the results of your doing so.

Background Western Australia

Background Deserts

Background Limited road access

Background Deserts Limited road access check points 2 0 points

Background Deserts Limited road access check points Ports

Background Pest and disease freedoms Codling moth (Cydia pomonella ) Oriental fruit moth (Grapholita molesta) Apple scab (Venturia inaequali)

Background – Australia’s quarantine system Quarantine continuum Partnership States/Territories Interstate trade National International trade

Background – Australia’s quarantine system Memorandum of Understanding Agreement Enables SPS compliance Consistency

Background – WA Plant Biosecurity State pest risk analyses Market access National pest risk analyses

Background – WA Plant Biosecurity Important considerations integration of consequences and PEES impact of volume multiple pathways

The Model - Features Enhances existing methodology Incorporates variable input data trade volume complex scenarios multiple pathways Pest initiated is best

The Model - Pathway Simplistic schematic Pest Present in Source Orchard Yes = Imp1 No = 1 - Imp1 Harvested Fruit Infected Yes = Imp2 No = 1 – Imp2 Pest Survives Pack House Yes = Imp3 No = 1 – Imp3 Pest Survives Transport Yes = Imp4 No = 1 – Imp4 Pest Survives Quarantine ClearanceNo = 1 – Imp5 Yes = Imp5 Importation of Pest P1 Proportion of Fruit Purchased by Retailers P2 Proportion Purchased by Consumers from Retailers P3 Proportion of Fruit Discarded as Waste P4 Pest Viability Viable Waste from Consumers Exp1 - Exposure o f Commercial Hosts PPD c Partial Probability of Distribution to Commercial Hosts Partial Probability of Establishment PPD h Partial Probability of Distribution to Household Hosts PPD w Partial Probability of Distribution to Wild Hosts Exp2 - Exposure o f Household Hosts Exp3 - Exposure o f Wild Hosts Importation Distribution

The Model – Output Years before 1 st introduction = 1+RiskGeomet(PEEannual)

1+RiskGeomet(PEEannual)

Introduction frequency = 1/PEEannual The Model – Output

1/PEEannual

Volume and risk

Non linear high unit risk rapid increase at low volumes low unit risk rapid increase occurs later Consider all pathways and total volume Monitor phytosanitary measures efficacy Volume and risk

Introduction frequency - applications Risk Communication Tangible ALOP Defining Consequences integrating consequences with PEES how often is too often?

Introduction frequency - applications Management strategies phytosanitary measures efficacy Non-SPS application development of policy business planning strategy planning to minimise impact of trade

Where to from here? Validation Check model assumptions using data collected during 2 seasons review and release model Risk assessment Link between introduction frequency and consequences ALOP

The plant biosecurity team Director Plant Biosecurity – Dr Shashi Sharma Activity Specialist/Policy – Mr Mark Stuart Pathologist/modelling – Ms Nichole Burges Pathologist – Dr Satendra Kumar Entomology/climate modelling – Mr Marc Poole Entomology – Dr John Botha Biometrics – Ms Jane Speijers Policy – Ms Simone Tuten