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PBCRC 2110 Design and Evaluation of Targeted Biosecurity Surveillance Systems

Michael Renton and Maggie Triska

Plant Biosecurity Cooperative Research Centre

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Problem being addressed

Optimal surveillance design

(what’s the best way to look for something you don’t want to find)

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Problem being addressed

What is the best design for a surveillance system?

- Number of samples (traps etc)

- Location of sampling

- Frequency of sampling

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General methods specific applications

Three case studies

- Grape phylloxera

- PCN

- Fruit fly

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Grape phylloxera

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Grape phylloxera

High virulenceLow virulence

High suitabilityMedium suitability

Low suitability

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Grape phylloxera

Standard

↑↓ Density

Target high

suitability soil

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Grape phylloxera results

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Grape phylloxera results

Surveillance design based on soil types

- More efficient

Sampling density

- Relatively minor effect

Low virulent genotypes in low suitability conditions

- Many, many years before detection

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Vic statistical areas

Properties

Movement

Fresh Seed

PCN

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Spread simulations

Infested Detected

- Predict spread under different surveillance strategies

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PCN results

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PCN summary

Survey density ↑

- ↓ infested properties

Survey arrangement (with fixed density)

- variation between strategies

Detection

Surveillance: Region +

Random

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Fruit fly

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Individual

trees

Orchards

High risk

introduction

sites

Initial

Incursion

Initial

Incursion

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Surveillance (trapping) designs

grid random

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adhockmeans

firstfirst

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Results!

Better!

1 10 100 1000 10000

N trees

pro

ba

bility

0.0

00

10

.00

10

.01

0.1

1

gridadhoc

firstfirstkmeansrandom

0 100 200 300 400

days to detection

pro

ba

bility

0.0

00

10

.00

10

.01

0.1

1

gridadhoc

firstfirstkmeansrandom

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NZ MPI: Q-fly case study

Data from 2015 Q-fly incursion

Analysis of surveillance to confirm eradication

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Open questions and next steps

Practicality and adoption of designs?

Ease of use (training module for fruit fly)

Ease of generalisation

- to new locations, species, organisms, situations…

Effects of biology and spread?

Effects of better detection?

- Better traps (sooner, longer distances, mobile, adaptive)

- Better sampling/diagnostic methods

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Thanks!

biosecurity built on science

biosecurity built on science

biosecurity built on science

Grape phylloxera

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PCN

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biosecurity built on science

Probability of detection from active and passive surveillance increasing as a function of time since first infestation of a field.

0 5 10 15

0.0

0.2

0.4

0.6

0.8

1.0

t

p

active

passive

Detection and diagnostics?

1 5 10 50 500 5000

N trees

pro

ba

bility

0.0

00

10

.00

10

.01

0.1

1grid

adhocopt_timeopt_ninfs

firstfirstkmeansrandom