Design and Evaluation of Targeted Biosecurity Surveillance Systems

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PBCRC 2110 Design and Evaluation of Targeted Biosecurity Surveillance Systems

Michael Renton and Maggie Triska

Plant Biosecurity Cooperative Research Centre


Problem being addressed

Optimal surveillance design

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


Problem being addressed

What is the best design for a surveillance system?

- Number of samples (traps etc)

- Location of sampling

- Frequency of sampling


General methods specific applications

Three case studies

- Grape phylloxera

- PCN

- Fruit fly


Grape phylloxera


Grape phylloxera

High virulenceLow virulence

High suitabilityMedium suitability

Low suitability


Grape phylloxera

Standard

↑↓ Density

Target high

suitability soil


Grape phylloxera results


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


Vic statistical areas

Properties

Movement

Fresh Seed

PCN


Spread simulations

Infested Detected

- Predict spread under different surveillance strategies


PCN results


PCN summary

Survey density ↑

- ↓ infested properties

Survey arrangement (with fixed density)

- variation between strategies

Detection

Surveillance: Region +

Random


Fruit fly


Individual

trees

Orchards

High risk

introduction

sites

Initial

Incursion

Initial

Incursion


Surveillance (trapping) designs

grid random


adhockmeans

firstfirst


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



NZ MPI: Q-fly case study

Data from 2015 Q-fly incursion

Analysis of surveillance to confirm eradication


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


Thanks!




Grape phylloxera


PCN



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


Science

Design and Evaluation of Targeted Biosecurity Surveillance Systems