Session 5: Decision making for eradication and quarantine zones

PowerPoint Presentation

Decision making for surveillance and quarantine

Grant Hamilton & Peter BaxterPlant Biosecurity Cooperative Research Centre

biosecurity built on scienceWhat is the problem?Urgent need for efficient and effective methods to plan surveillance and quarantineIncorporate multiple layers of data to better plan surveillance and qzones

Decisions in the face of uncertaintyinitially with limited data how to obtain new data how to incorporate new data into the decision response

Briefly summarize the specific problem or issue that your research is addressing?

biosecurity built on science

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What are we doing about it?How will your research address the problem or issue?create applied methods that support data capture and decision makingUAVs effective flight paths Optimising methods for surveillance, qzones risk maps and networks Spatial analysis- Qfly natural barriers


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Planning effective surveillance for detectionUAVUnmanned aerial vehicle (UAV) surveillance how do flight-plans perform faced withdetection errorsorganisms spatial ecology

Best performing UAV flight plansunderlying detection erroraggregation

Infestation intensityBaxter & Hamilton (2015). MODSIM2015: 1393-1398Fine-tuning of unmanned aerial surveillance for ecological systems. high+fast


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Range of recommendationsegSmall detection error, high density, regular spatial pattern = Low and Fast flightsDetecting an incursion High and Fast flights (for moderate to low detection error)

biosecurity built on scienceResultsExample of incursionresponseRandomised risk-weighted search

Sites+ Infected SearchingX DetectedIf ALWAYS looking nearInfected property, sub optimal result

Ensure surveillance is not toonarrowly focused

Next step is to translate surveillance into..


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Surveillance prioritisation through time. week: 100 300 400

Priortzn basis:

Risk = proximity to known infections

Risk = Estimated natural & social spread

spread of infection

biosecurity built on scienceRun FUSIMOD till about line 160 (to get farms and connection matrices set up)Put in a stop at ~line (if mod (t, 100) ==0) for those, do:K>> [~,farmRanks]=sort(rankedFarms);K>> mapFarms(farmXY, farmArea, farmRanks)K>> axis([-10 110 -10 110])K>> set(gca, 'xticklabel','', 'yticklabel','')

K>> mapFarms(farmXY, farmArea, sum(farmSocMat,2))K>> axis([-10 110 -10 110])7

Adding extra layers: transmission risk and control using networksRisk networks and Incursion Response rulesMultiple networksHuman:socio-economic ( informed by tracing data)roadagronomists as vectors

Abiotic:environmental gradient extreme-event mixing

15 farms; 3 agronomists cover 10 farms


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Farm networkQuarantine approachesShows extra effect of agronomists (note increased scale of connection strength)


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Farm networkQuarantine approachesShows extra effect of agronomists (note increased scale of connection strength)


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Networks of Panama tracing

Real tracing data from the Panama incursion: 336 tracing connections

Data manipulation for this:Excluded non-banana properties Recategorised into 5 types of connection. Listed by decreasing risk:Plant material e.g. planting material, debris Equipment sharinge.g. irrigation, earth-movers People movemente.g. crop consultants, packers Geographic links e.g. proximity, shared drainage line Othere.g. rubbish collection, fuel delivery of

Randomly assigned positions in space to preserve anonymity


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Tracing through a farm networkShared plant material only


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Tracing through a farm networkEquipment sharing only


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Tracing through a farm networkGeographic links


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Tracing through a farm networkCombined links assuming all bi-directional


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Transmission risk and controlRisk networks and Incursion Response rulesQuarantine rules from human network links:

Blanket:moderate widespread restrictionsTargeted:IPs isolated, weaker widespread restrictions Path-based:reduce all road and agronomist linksLink-based:reduce connections from sites within fixed radius of IPs

Surveillance Risk-based heuristic to optimised search method (Parnell et al. 2014)

biosecurity built on scienceLink-based: Half median distance between all connections in the network based on real data. Still need distance. Reduce p(cnxn) by 50% 16

ResultsNo management(meanSE, 1000 runs/simulation)Infection intensity,hectares(fungal load)

# farms infected

biosecurity built on sciencething=infx225; round(mean(sum(sum(thing)))), round(mean(sum(sum(thing>0))))17

ResultsEffect of different quarantine measures(meanSE)BlanketTargetedPath-basedLink-based

Infection intensity,hectares

# farms infectedQuarantine:reduce connections from sites within fixed radius of IPs


ResultsEffect of different quarantine measures(meanSE)BlanketTargetedPath-basedLink-based

Infection intensity,hectares

# farms infectedQuarantine:

For latest results Peter Baxter at 1:30pm Thursday


QFLY population genetics project:

Image: www.goulburnrivervalley.com.au/stakeholderinformation/are-you-giving-accurate-information-about-fruit-fly Aim: to examine the population genetic structure of QFLY in the former Fruit Fly Exclusion ZoneIf genetic structure exists, link barriers to gene flow with landscape features Identify putative source(s) of current infestation

biosecurity built on scienceQfly Genetics: progress to date10 microsatellite markers screened279 flies from 23 siteshigh levels of polymorphism for most lociLocus Ho Ht# AllelesAllelic richnessBt32 0.753 0.830 16 7.034Bt11 0.699 0.738 9 4.7341.7.7 0.035 0.035 5 1.311Bt4.1A 0.306 0.522 6 2.403Bt15 0.429 0.694 5 3.953Bt14 0.559 0.587 5 3.861Bt10 0.469 0.558 9 4.082Bt1.7 0.642 0.736 15 5.515Bt8.6A 0.733 0.847 22 7.221Bt17 0.703 0.720 6 4.305

SiteSample SizeBilbul6Cobram South22Coleambally2Corbie Hill25Darlington Point13Griffith9Hanwood11Hillston18Kialla Central16Leeton14Merbein27Mooroopna23Murrami5Narrandera1Nericon9Paytners Sliding20Stanbridge5Stoney Point5Summerton Park21Tharbogang12Whilton6Yanco2Yenda7

NB: Blue sites located in Victoria

biosecurity built on scienceResults: population genetic structure analysis

Stoney PtStanbridgeYendaYancoBilbulCobram SthColeamballyCorbie HillDarlington PtGriffithHanwoodHillstonKialla CentralLeetonMerbeinMooroopnaNericonNarranderaPaytners SlidingSummerton PkWhiltonTharbogangMurrami2 population genetic clusters identified in structure analysis

biosecurity built on sciencePopulation genetic structure analysis

Paytners SlidingStanbridgeStoney PointYancoYendaTharbogangWhiltonMurramiNarranderaNericonHanwoodHillstonLeetonColeamballyDarlington PtGriffithBilbulCorbie Hill

Riverina Protected Areas

Each pie graph shows the proportion of individuals with that had a proportion of membership of >0.8 to one of the 2 identified clusters Grey = unssigned (

Session 5: Decision making for eradication and quarantine zones

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Transcript of Session 5: Decision making for eradication and quarantine zones