Table 2 The time delay until 20% of a herd shows clinical signs of infection with foot and mouth disease, the daily probability that each farm type will report the occurrence of clinical
Trang 1Preventive Veterinary Medicine 128 (2016) 78–86
j ou rn a l h om ep a ge :w w w e l s e v i e r c o m / l o c a t e / p r e v e t m e d
a Animal Health Policy Branch, Commonwealth Government – Department of Agriculture, GPO Box 858, Canberra, ACT 2601, Australia
b Crawford School of Public Policy, Crawford Building (132), Lennox Crossing, Australian National University, Canberra, ACT 0200, Australia
Article history:
Received 8 May 2015
Received in revised form 28 January 2016
Accepted 19 April 2016
Keywords:
Foot and mouth disease
Surveillance
Early detection
Simulation modelling
Thisstudyaimedtoevaluatestrategiestoenhancetheearlydetectionoffootandmouthdisease incur-sionsinAustralia.Twostrategieswereconsidered.First,improvingtheperformanceofthecurrent passivesurveillancesystem.Second,supplementingthecurrentpassivesystemwithactivesurveillance strategiesbasedontestinganimalsatsaleyardsorthroughbulkmilktestingofdairyherds.Simulation modellingestimatedtheimpactofproducereducationandawarenessbyeitherincreasingthedaily prob-abilitythatafarmerwillreportthepresenceofdiseasedanimalsorbyreducingtheproportionoftheherd showingclinicalsignsrequiredtotriggeradiseasereport.Bothincreasingtheprobabilityofreporting andreducingtheproportionofanimalsshowingclinicalsignsresultedinincrementaldecreasesinthe timetodetection,thesizeandthedurationoftheoutbreak.Agoldstandardsysteminwhichall pro-ducersreportedthepresenceofdiseaseonce10%oftheherdshowedclinicalsignsreducedthemedian timetodetectionoftheoutbreakfrom20to15days,thedurationofthesubsequentoutbreakfrom53
to42daysandthenumberofinfectedfarmsfrom46to32.Bulkmilktestingreducedthemediantime
todetectionbytwodaysandthenumberofinfectedfarmsbysixbuthadnoimpactontheduration
oftheoutbreak.Screeningofanimalsatsaleyardsprovidednoimprovementoverthecurrentpassive surveillancesystemalonewhilehavingsignificantresourceissues.Itisconcludedthatthemosteffective waytoachieveearlydetectionofincursionsoffootandmouthdiseaseintoVictoria,Australiaistoinvest
inimprovingproducerreporting
CrownCopyright©2016PublishedbyElsevierB.V.Allrightsreserved
1 Introduction
Footandmouth disease(FMD)isoneof themostinfectious
diseasesofdomesticlivestock(OIE,2012).FMDisendemicin
two-thirdsoftheworld(GrubmanandBaxt,2004;Kompasetal.,2015)
whereitcausesannuallossesofUS$6.5–21billion(Knight-Jones
andRushton,2013).Increasinginternationalmovementsandtrade
presentanon-goingthreattoFMD-freecountries.Inthepast15
years,therehave beena numberofoutbreaksofFMDin
previ-ouslyfreecountriesdespitetheapplicationofstringentquarantine
measures.Theseoutbreaksresultedinestimatedfinanciallosses
ofmorethanUS$1.5billion(Knight-JonesandRushton,2013)and
Abbreviations: CVO, Chief Veterinary Officer; FMD, foot and mouth disease;
GSAT, general surveillance assessment tool; IP, infected premises; PCR, polymerase
chain reaction.
∗ Corresponding author.
E-mail addresses: iain.j.east@agriculture.gov.au , iain.east@gmail.com (I.J East).
substantialdisruptiontotheinternationallivestocktrade(Blayney
etal.,2006)
InthefaceofthecontinuingthreatofFMDintroduction,early detectionofanincursionisofparticularimportancebecausethe longerthetimetodetectionandthelargerthesizeoftheoutbreak
at detection, the more difficult is the task of disease eradica-tion(Carpenteretal.,2011;Matthews,2011).Acommonformof surveillanceusedtodetectdiseaseincursionsispassive surveil-lance;theobservationand reportingof clinicalsignsofdisease
inanimalsbyanimalhealthprofessionals,para-professionals, ani-malowners,producers,processorsandothersacrossthelivestock industries(Hoinville,2011).Keyobservationpointsforlivestock include thefarm, themarket/saleyardand theabattoir Passive surveillancetendstodetectdiseasesassociatedwithunusualor obviousclinicalsigns.Whileithasitslimitationsintermsof pro-vidingrepresentativeinformationonpopulations,intimelinessof detectionandinhavingpoorsensitivity,itcanbeaveryeffective methodofidentifyingnewandemergingdiseases(Langstaff,2008) Previousqualitativestudieshavealsoshownthatthetimebetween firstclinicalappearanceofdiseaseandtheactualreportingofthat http://dx.doi.org/10.1016/j.prevetmed.2016.04.009
0167-5877/Crown Copyright © 2016 Published by Elsevier B.V All rights reserved.
Trang 2Fig 1 Map of Victoria (the study area) showing major dairying areas (shaded areas) and the location of smaller pig farms (•).
diseasebyfarmersisoftentoolong,resultinginextensivespread
ofthedisease(Elbersetal.,1999;Elbersetal.,2010).Reportingof
diseasebyproducersislimitedbyanumberoffactorsincluding
inabilitytorecognisethedisease(Hoppetal.,2007),the
poten-tialdeleteriousimpactofreportingdiseaseontheindividualfarm
throughquarantine,stampingout,etc.(Elbersetal.,2010)anda
lackoftrustingovernment(Palmeretal.,2009;Elbersetal.,2010)
Anyactionsthatcouldovercomethesebarrierstoreportingcould
wellbeeffectiveinenhancingtheefficacyofpassivesurveillance
fordetectingdiseaseincursions
Theperformanceandreliabilityofthepassivesurveillance
‘sys-tem’inAustraliahasbeenofconcernforanumberofyears,largely
owingtoreductionsingovernmentexpenditureonagricultureand
areductionintheveterinaryservicesinruralareas(Nairnetal.,
1996;Frawley,2003;Matthews,2011).Similarconcernshavebeen
expressedinother countriesincludingtheUnitedStates (Bates
etal.,2003)andTheNetherlands(Klinkenbergetal.,2005)
ArecentreviewofAustralia’spreparednessforFMD(Matthews,
2011)foundthatthereisastrongpossibilitythatanincursionof
FMDmaynotbereadilydetectedduetoarangeoffactors
Mod-ellingstudiesinAustralia(Martinetal.,2015;Eastetal.,2016)have
indicatedthatexpectedtimestodetectionwouldbe20–33days
withanupper 90thconfidenceinterval of 22–47days,
depend-ingonregion.Thepredicteddelaytodetectionissimilartothose
observedinrecentoutbreaksinothercountries(Anderson,2002;
Boumaetal.,2003;Yoon etal.,2013).It isthereforeofinterest
toexamine whetherpotentialexiststoimprove time to
detec-tionthroughintroducingactivesurveillance,usingnewmethodsof
surveillanceorenhancingtheexistingpassivesurveillancesystem
Saleyards and markets have been recognised as important
amplifying points for FMD because of their potential facilitate
rapidspreadof infectionover wideareas(Mansleyetal.,2003;
Animal Health Australia 2014a) Activesurveillance using
real-timedetectionsystemstoidentifyFMDatsaleyardswasproposed
byBatesetal.(2003)asawaytopreventdisseminationof
dis-easethroughtransportofinfectedanimalsawayfromthesaleyard
Hernández-Joveretal.(2011)estimatedthesensitivityofthe
cur-rentsurveillancesysteminplaceatAustralianpigsaleyardsand
abattoirsfordetectingFMDasnomorethan0.35indicatingthat
potentialforimprovementtosaleyardsurveillanceexists
Newmethodsofsurveillancemayarisethroughdevelopment
ofnewtechnologiesandoneexampleofthisisthedevelopmentof
bulkmilktestingforFMD(Reidetal.,2006;ThurmondandPerez,
2006).Footandmouthdiseasevirusisdetectableinthemilkof infectedcowsfor1–3daysbeforeclinicalsignsofinfectionappear (Blackwellet al.,1982;Reid etal.,2006).Thisobservation pro-videspotentialtodetectdairycows infectedwithFMDprior to theappearanceofclinicalsigns;anearliertimepointthan pos-siblethroughpassivesurveillance.Thetestsdevelopedallowfor thedetectionofFMDvirusinsamplesdilutedupto1in104(Reid
etal.,2006)andthiswouldallowtestingofbulkmilksamplesafter arrivalatamilkprocessingfacility.Giventhesedevelopmentsin PCRdiagnostictechnologyfordetectingFMDvirusinmilk sam-ples,thefeasibilityoftestingmilksamplesforFMDisofparticular interestbecausesamplingschemestocollectbulkmilkarealready
inplaceforanumberofqualityassuranceprograms
Thispaperaimstoexaminethepotentialforimprovingearly detectionofFMDinVictoria,Australiathrough:
1.Enhancingtheperformanceofthecurrentpassivesurveillance system througheducation campaigns that increase producer awarenessofdiseaseandthecapacitytorecognisediseased ani-mals
2.Activesurveillanceprogramsatsaleyards
3.Activesurveillanceusingbulkmilktesting
Todoso,weusedaspatiallydynamicepidemiologicalmodelfor FMDinAustralia(GarnerandBeckett,2005)toassesstheimpactof theseprogramsonthetimetodetectionbeforeanFMDoutbreak
isreportedandthesizeanddurationoftheoutbreakatthetime
ofreporting.Issuesinfluencingtheeffectivenessofthesestrategies arealsodiscussed
2 Materialsandmethods 2.1 Studyarea
ThestudyareaforthisprojectisthestateofVictoria(Fig.1) wherethetemperate,climateandhigherrainfallallowmore inten-sivefarmingthanmuchoftherestofAustralia.VictoriaisAustralia’s largestfoodandfibreexportingstateandisthecentreofAustralia’s dairyproduction.Ithas9.2%ofthenationalbeefcattlepopulation, 63.6%ofthedairycattlepopulation,24.8%ofthepigpopulation and21.3%ofthesheeppopulation(ABARES,2014).Thestudyarea contains42,279farmswithFMDsusceptiblespeciescategorised intooneofeightdifferenttypes(seebelow)forthepurposesof
Trang 380 M.G Garner et al / Preventive Veterinary Medicine 128 (2016) 78–86
Table 1
The number of farms by type in the study area.
dis-creteareasofthestate(Fig.1).Becauseofthemildclimate,higher
stockingrates,relativelyhighhumanpopulationdensityand
prox-imitytoairportsandseaports,Victoriaisconsideredtobeahigher
risk area of Australia for FMD introduction,establishment and
spread(Eastetal.,2013)
2.2 Diseasespreadmodelling
The Australian Department of Agriculture’s FMD model
AusSpreadwas used tosimulate outbreaks of FMD.AusSpread
(GarnerandBeckett,2005;Eastetal.,2014a,b;Garneretal.,2014)
isastochasticspatialsimulationmodelinwhichFMD
transmis-sionis modelled through five discrete pathways:farm to farm
animalmovements,localspread(infectionoffarmswithinclose
geographical proximity by unspecifiedmeans), indirect contact
(viacontaminatedfomitesoranimalproducts),animalmovements
viasale-yardsormarketsandwind-bornespread.Eightdifferent
farmtypesarerecognisedinthemodelincludingspecialistbeef,
dairy,sheep,smallpig,largepig,mixedbeefand sheep,feedlot
producersandsmall-holders.Small-holdersaresmalllandowners
withlivestock,whoareoftensubcommercialandhavelifestyle
as a key motivator The model incorporates the attributes and
spatiallocationsofindividualfarms,saleyards,weatherstations,
localgovernmentareasandvariousotherfeaturesoftheregional
environment.AusSpreadisconfiguredtosupporttherangeof
con-trolmeasuresdescribedinAustralia’semergencyanimaldisease
responsearrangements(AnimalHealthAustralia,2014a).The
dis-ease control options available in themodel include a national
livestockstandstillperiodandsubsequentmovementrestrictions
inRestrictedAreas(arelativelysmalllegallydeclaredareaaround
infectedpremisesanddangerouscontactpremisesthatissubject
todiseasecontrols,includingintensesurveillanceandmovement
controls)andControlAreasalegallydeclareddisease-freebuffer
areabetweentheRestrictedArea anduninfected areas(Animal
HealthAustralia,2014b)aroundinfectedpremises(IPs),
surveil-lanceandtracing,andstampingoutofIPs.Pre-emptivecullingof
propertiesaroundIPsand/ortraceddangerouscontactpremises
orvaccinationmayalsobeconsidered.Tosupportthisstudy,an
additionalmodulewasaddedtoAusSpreadtosimulatedetection
ofFMDthroughthepassivesurveillancesystem.Thismodulehas
nowbeenincorporatedintoAusSpreadsotheuserhasachoice
ofdetermining when thefirst detection afteran incursionwill
bemade–eitherfixedtimeorthroughpassivereporting.Passive
reportingwasimplementedbyapplyingprobabilitiesthatsuspect
FMD,basedonclinicalsignsofdisease,wouldbereportedby
live-stockowners, inspectorsatsaleyardsor inspectorsatabattoirs
Theprobabilityofreportingwasconditionalonaminimum
clin-icalprevalenceonaninfectedfarm.Aseriesoftimestepstoallow
forinvestigation,confirmationandreportingtotheChief
Veteri-naryOfficer(CVO),wereaddedtodeterminewhenanemergency
diseaseresponsewouldbetriggered.Theapproachisdescribedin
moredetailbelow
Table 2 The time delay until 20% of a herd shows clinical signs of infection with foot and mouth disease, the daily probability that each farm type will report the occurrence
of clinical signs and the number of days for which more than 20% of the herd show clinical signs.
Farm type Minimum time
until 20% of herd shows clinical signs
Daily probability
of reporting
No days above 20% clinical threshold
authority
developmentofaspreadsheettool(GeneralSurveillance Assess-mentTool– GSAT)thathasbeenusedtoassesstheefficacyof generalsurveillancefordetectingincursionsoflivestockdiseases
inAustraliabasedoninputsfromjurisdictionalveterinaryservices Consistentwiththiswork,weassumedageneralthreshold clini-calprevalenceof20%inhisherdfortheownertonoticeandseek assistance.AsFMDspreadsatdifferentratesinthedifferentfarm typesthistranslatesintovaryingminimumtimestoreportand dailyprobabilitiesofreporting(0.005–0.884)byfarmtype.Table2 summarisesthedailyprobabilityofreportingbyfarmtype,the durationofperiodsoverwhichclinicalsignscouldbereportedand theexpectedtimefromfirstinfectionuntiltheclinicalthresholdfor possiblereportingisreached.Probabilityestimateswerederivedby
aseriesofexpertpanelsassembledtodevelopparametersforthe GSAT,withtheexpectedtimesandclinicalperiodsderivedfrom modellingFMDtransmissionwithintheherd(Martinetal.,2015) Foreach ofthetwelveproductionregionsfoundinAustralia (East et al., 2013), a separate expert panel was convened and wascomprisedofsixtoeightanimalhealthspecialistsfromeach
ofthestate\territorygovernmentswithlandlocatedwithinthat
Trang 4Table 3
The probabilities that an inspector would notice and report an FMD infected
con-signment (assuming ≥ 20% clinical prevalence in the source farm).
Abattoirs
Saleyards
Table 4
The estimated probabilities and times for individual steps of the reporting chain
for foot and mouth disease being reported to the chief veterinary officer
(assum-ing ≥ 20% clinical prevalence in the source farm).
Farmer observes stock 0.142–0.959 1–30 days
Farmer recognises clinical signs 0.30–0.97 1 day
Farmer contacts vet 0.55–0.95 1 day
Vet investigates 0.95 1–2 days
Vet suspects EAD 0.92 –
Samples submitted to lab 0.84 1
samples tested 0.84 2
FMD detected 0.96 –
a Variable by animal species and by herd type, for detailed figures see Martin et al.
(2015) Supplementary data Table 1.
b Time from becoming infectious to reaching 20% clinical prevalence.
productionregion.For thestudyareautilisedinthis paper,the
VictorianGovernment,DepartmentofPrimaryIndustriesalso
con-ductedaproducersurveytoinformtheprobabilityestimatesused
inthisstudy(resultsnotpublished)
Inadditiontoon-farmreportingbytheowner/manager,
suspi-cionofFMDassociatedwithclinicalsignscouldalsobereported
byanabattoirorsaleyardinspectoraspartoftheirnormal
inspec-tionrole.Probabilitiesthataninspectorwouldnotice,recognise
andreportanFMDinfectedconsignment(Table3)werederivedby
aseriesofexpertpanelsassembledtodevelopparametersforthe
GSAT(Martinetal.,2015)
Tables2and3providethebasisfordeterminingwhether
sus-pectFMDwillberecognisedandinvestigated.However,several
additionalstepsarenecessarytoensurethatFMDisconfirmedand
reportedtotheCVO.TheseadditionalstepsarelistedinTable4
Again,theseestimatesforthesestepswerederivedbyaseriesof
expertpanelsassembledtodevelopparametersfortheGSATand
wereassumedtobeconstantforallfarm typesandgeographic
regions(Martinetal.,2015)
Estimatesofthetimeelapsedateachstepofthepassive
surveil-lancechainwerederivedfroma reviewoftheliteratureandby
theseriesofexpertpanelsassembledtodevelopparametersfor
theGSAT (Martin etal., 2015).Thisexpected timerequired for
investigationandnotificationoftheCVOwillvarydependingon
thenatureofthereportandthefollowingvalueshavebeenused:
Farmerreport–5days,Saleyardinspection–4daysandAbattoir
inspection–3days.ThefinalvaluesusedareshowninTable4.In
Australia,ifanotifiablediseaselikeFMDissuspected,jurisdictional
animalhealthserviceshavethelegalinstrumentstoquarantine
thesuspectedpremises.Australia’spolicyistoalsoimplementa
nationallivestockstandstillfromthetimeofdiagnosisofFMDor
onstrongsuspicionofthedisease(AnimalHealthAustralia,2015)
2.4 Enhancingthe‘passive’surveillancesystem The reporting of suspect disease by livestock owners could
beimprovedbyincreasingtheirawarenessofseriousdisease,by increasingthefrequency and extentof livestockinspectionsby owners,andbyimprovingwillingnessofownerstohaveproblems investigated(e.g.byagovernmentorprivateveterinarian) Educa-tionandawarenessprogramscouldbegeneralisedortargetedto specificindustrysectors.Fromamodellingperspective,thiscanbe representedbyareducedclinicalthresholdforreportingtooccur and/oranincreaseddailyprobabilitythatalivestockownerwith clinicallyaffectedlivestockwouldreport.However,itisdifficultto predicttheimpactofawarenessprogramsonproducerbehaviour
Areviewofextensionandproducereducationprogramsconducted
inAustraliainrecentyearssuggeststhatthebestprogramsresult
inanuptakeofnewfarmingpracticesofonly30–40%of partici-pants(Larsenetal.,2002;PriceandHacker,2009;Huntetal.,2011) Althoughitcannotbeassumedthatproducerswouldrespondinthe samewaytobiosecurityawareness,intheabsenceofother infor-mationwebelievethatthisprovidesaplausibleupperestimate
ofwhatmightbeexpected.Swillfeedingtopigsisthemostlikely opportunityforFMDtoestablishinAustralia(Matthews,2011),we evaluatedaneducationcampaigntargetedatthesmall-to-medium pigproducerstowhich30%ofproducersresponded;thedaily prob-abilityofreportingbyapigproducerwithaherdshowingclinical signsconsistentwithFMDincreasedfromabaselineof0.18to0.48 2.5 Activesurveillanceatsaleyards
Activesurveillance programsfor diseaseslikeFMD couldbe basedontestingsamplesofanimalssubmittedforsale.Thistesting couldbebasedonrandomortargetedsamplingregimes.Inthe for-mercaseanimalswouldbeselectedatrandomfromthepopulation
onanygivensaleday.Inthelattercase,animalswouldbeselected forsamplingonthebasisofsomeformofscreeningproceduree.g animalsshowingsignslikelamenessorthroughinfra-red thermog-raphy(Rainwater-Lovettetal.,2009).Theprobabilitythatasingle infectedfarmsubmittinganimalstoasalewouldbedetectedwas estimated,basedonsimplerandomsampling,assuming20,50or
100animalsaretestedpersaleandFMDtestsensitivityof97%(King
etal.,2006).Theprobabilitythatasingleinfectedfarmwouldbe detectedwasalsoestimatedassumingthesaleyardpopulationis firstscreenedwithinfraredthermography,whichwasassumedto haveasensitivityof61.1%andaspecificityof87.7%( Rainwater-Lovettetal.,2009)
2.6 Bulkmilktesting Althoughbulkmilktestingshowsgoodpotentialasascreening testforFMD,thereisnocommerciallyavailabletestatthistime Forthisstudy,wemadethefollowingassumptions:
•alldairyfarmswillbetestedeveryday(milkiscollecteddaily fromdairyfarmsinthestudyregion).Aresultisavailablethe nextdayafterthemilkiscollected
•testingisatthetankerlevel
•thePCRhasananalyticalsensitivityof10−2.5or10−3.Withan averagemilkingherdsizeof225,thismeansfourortwoinfected cowsperherd,assumingaminimumofoneinfectedherd con-tributingtoatanker.Ourmodellingusedthreeinfectedcowsas thefarmlevelthresholdfordetection(∼10−2.6)
•thediagnosticsensitivityofthemilkPCRtestis95%
•thereisatwodaydelayfromwhenmilkistesteduntilFMDis confirmed–toallowfortracebackofindividualfarmsand con-firmatoryinvestigation/testing
Trang 582 M.G Garner et al / Preventive Veterinary Medicine 128 (2016) 78–86
2.7 Outbreakscenarios
ThesourceoftheFMDintroductionwasassumedtobe
contam-inatedfoodbroughtintoAustraliabyatravellerreturningfrom
overseasandthen(illegally)fedtopigs.Thisisconsideredtobe
themostlikelywayforFMDtoestablishinAustralia(Matthews,
2011).Thiswasassumedtooccuronasmallerpigfarmsincein
Australialargerpigfarmstypicallyhavehighlevelsofbiosecurity
(Hernández-Joveretal.,2012).Theintroductionwasassumedto
occurinMay,whencoldandwetconditionswouldfavourFMD
virussurvivaloutsideahost.Foreachmodeliteration,apigfarm
oftheappropriatetypewasrandomlyselectedasthesourcefarm
toinitiateanoutbreak.Thedistributionofsmallerpigfarmsinthe
studyareaisshowninFig.1
2.8 Studydesign
AusSpreadwasconfiguredsothatthefirstdetectionofFMDwas
dynamicallydetermined,takingintoaccounttheabovedetection
parameters.Diseasewasintroducedintoarandomlyselectedsmall
pigfarm(<500pigs)andthemodelwasrununtileitherdisease
wasdetectedandadiseaseresponseprograminitiatedordisease
spontaneouslydiedout
Elevenpotentialsurveillancestrategieswereexamined:
1.Baselinepassivesurveillance–thestatusquowherethereisa
dailyprobabilityofareportingbyaproducerwithaninfected
herd,when20%ormoreoftheanimalsshowingclinicalsigns
ofinfection.Thedailyprobabilityisafunctionoffarmtypeand
isshowninTable2
2.Goldstandard –a hypothetical‘perfect’surveillancesystem
wherethedailyprobabilityofreportingbyallfarmersis1.0
when10%ormoreoftheiranimalsshowclinicalsignsof
infec-tion
3.Passive120 –thedailyprobabilityof small-to-mediumpig
farmersreportingsuspectdiseaseis1.0,ifaminimumof20%
oftheiranimalsshowclinicalsigns
4.Passive110 –thedailyprobabilityof small-to-mediumpig
farmersreportingsuspectdiseaseis1.0,ifaminimumof10%
oftheiranimalsshowclinicalsigns
5.Passive15 – the daily probability of small-to-medium pig
farmersreportingsuspectdiseaseis1.0,ifaminimumof5%
oftheiranimalsshowclinicalsigns
6.Enhanced passive surveillance – 30% of producers in the
small-to-mediumpigproductionsectorrespondtoan
aware-ness/educationcampaignandthedailyprobabilityofreporting
byasmall-to-mediumpigproducerwithaherdshowing
clin-icalsignsconsistentwithFMDincreasesfrom0.18to0.48
7.Saleyard20 –anactivesurveillance systemis implemented
where20 randomlyselectedanimalsat eachcattlesale are
testedbyPCRforinfectionwithFMD.Thetesthasasensitivity
of0.97andaspecificityof1.0
8.BMT1–bulkmilktestingeveryday
9.BMT2–bulkmilktestingeverysecondday
10.BMT3–bulkmilktestingeverythirdday
11.Integratedsurveillance(BMT1indairyareas,enhancedpassive
surveillanceinnon-dairyareas)
Twohundrediterations of each strategy wererun.For each
iteration,thefarmtowhichdiseasewasintroducedwasselected
randomlyfromamongthe163small-to-mediumpigfarmsin
Vic-toria.WhenFMDwasconfirmedaneradicationprogramconsistent
withAustralia’sresponsepolicyforFMD(AnimalHealthAustralia,
2014a)wasimplemented
Theoutputvariablesrecordedforeachiterationwere:
•TimefromintroductionuntilFMDconfirmedandtheCVOis noti-fied
•ProbabilitythatFMDestablishesandspreads(i.e.itdoesnotdie outbeforeitcanbereported)
•Durationoftheoutbreak(untildiseaseiseradicated)
•Numberofinfectedpremises
•Totalfarmsandanimalsculledtoachieveeradication 2.9 Statistics
All statistical calculations were conducted in STATA Inter-cooledsoftwarev11.0(StataCorpLP,CollegeStation,TX,USA).The surveillancestrategieswerecomparedusingtheFriedmantestfor comparisonofmultiplegroupsofmatcheddata.Posthocanalysisto identifydifferencesbetweenpairsofindividualstrategieswas con-ductedusingtheWilcoxonsignedrankstestwiththesignificance leveladjustedusingtheBonferronicorrection.Inaproportionof themodellingiterations,theFMDoutbreakdiedoutbeforethe out-breakwasobserved.Thisvariedfrom11%forthebaselinepassive surveillancetozerofortheGoldstandard.IterationswhereFMD diedoutbeforetheoutbreakwasobservedandreportedwerenot includedintheanalysis
3 Results 3.1 Currentandgoldstandardpassivesurveillancesystems ThecurrentBaselinepassivesurveillancesystemresultedina mediandelayfromdiseaseentryontotheindexfarmuntil detec-tionoftheoutbreakof20days.Themedianoutbreak lastedfor
53daysandresultedin46infectedfarms(Table5).Incontrast,a Goldstandardsystemwhereeveryfarmerreporteddiseaseassoon
as10%ormoreoftheiranimalsshowedclinicalsignsresultedina reductioninthemediandelaytodetectionof5days,inoutbreak durationof11daysandintotalfarmsculled(IPsanddangerous contactpremises)of14(Table5)comparedwithBaseline.These reductionswerestatisticallysignificant(p<0.05)
3.2 Enhancedpassivesurveillance Increasingtheprobabilityofreportingfrom0.18to0.48reduced themediandelaytooutbreakdetectionbythreedays(p<0.05), themediandurationoftheoutbreakbysixdays(p=N.S.)andthe mediannumberoffarmsrequiringcullingby11(p<0.05)(Table5)
Afurtherincreaseinthedailyprobabilityofreportingto1.0 (Pas-sive120)resultedinareductionofanadditionalonedayinthe delaytoreportingbutthesizeanddurationoftheoutbreakwere unchanged.Reducingthetriggerpointforreportingfrom20%of animalsshowingclinicalsignsto5%(Passive15)resultedinasix dayreductioninthedelaytooutbreakdetection,a12day reduc-tioninthedurationoftheoutbreakandareductionof20inthe numberoffarmsrequiredtobeculled(all,p<0.05)comparedto theBaselinestrategy
Ourmodellingresultsshowedthatwhenthevariousenhanced surveillancestrategiesarecompared withtheBaselinestrategy, theobservedreductionsindurationandsizeoftheoutbreakswere associatedpredominantlywiththeabsenceofverylargeoutbreaks (Fig.2).Thatis,inmanycases,outbreaksweresmallwithlimited spreadsoreducing timetodetectionhadlittleeffect.However, earlydetectionwasvery effectivein reducing thelikelihood of gettingalargeoutbreak.Ifthefourthquartileofresultsonlyare compared (Baseline passivewith Passive120 and Passive15), thenthetimetodetectionisreducedbytwoweeks,theduration
oftheoutbreakisreducedby24and33daysrespectivelyandthe
Trang 6Table 5
The delay to detection, duration and size of foot and mouth disease outbreaks [median (95% probability interval)] in Australia as a function of small pig producer reporting behaviour.
Surveillance PerformanceThreshold prevalence of diseaseDaily probability of reportingDelay to detection (days)Duration of outbreak (days) Number of properties culled
Gold standard 10 1 15 (15–18) b 42 (32–73) b 32 (5–199) b
Enhanced Passive 20 0.48 17 (15–24) b 47 (32–88) a,b 35 (6–254) b
Passive 1 20 20 1 16 (16–20) c 45 (33–70) b,c 37 (4–184) b
Passive 1 10 10 1 15 (15–18) d 42 (32–74) b,c 32 (5–183) b
Passive 1 5 5 1 14 (13–16) e 41 (31–67) c 26 (9–123) c
* Within each column, figures with the same superscript are not significantly different.
Fig 2 The number of farms culled during foot and mouth disease incursions in Australia when different methods of surveillance are applied.
Table 6
The delay to detection, duration and size [median (95% probability interval)] of the largest quartile of foot and mouth disease outbreaks in Australia using different surveillance systems.
Enhanced Passive 16 (15–25) b 53 (35–98) b 74 (18–360) b
Passive 1 5 14 (14–17) c 44 (32–77) c 57 (11–137) c
* Within each column, figures with the same superscript are not significantly different.
numberofpropertiesrequiringtobeculledreducedby64%and
72%respectively(p<0.05)(Table6)
3.3 Saleyardtesting
Testingof20randomlyselectedanimalsateachcattlesaledid
notimprovethemediantimetodetectionorthemediandurationor
sizeoftheoutbreakcomparedtotheBaselinepassivesurveillance
strategy(Table7)
Foranaveragesaleof1350animalswith72vendors,theaverage
consignmentsizewas19animals.Assumingonlyoneinfectedherd
withawithinherdprevalenceof20%(abovethis,baselinepassive
surveillancewouldtriggerareport),therewouldbefourinfected
animalsatthesale.DirectscreeningbyPCRwithasensitivityof
0.97andaspecificityof1.0requiredasamplesizeof733animals
toachieve95%confidenceofdetectinganFMDinfectedanimal
Initial screening with thermography (Se=0.611, Sp=0.877)
wouldresultinselectionofagroupoftwotothreeFMDpositive
animalsand165FMDnegativeanimals.SubsequentPCRtestingof
thissub-groupofcattlewouldrequireasamplesizeof109animals
toachieve95%confidenceofdetectingaFMDinfectedanimal These two strategies would require either 1.23 million or 183,000on-site,PCRtestsinrealtimeannually.Takingintoaccount logisticalissues,coverageandpossiblecostsassociatedwith sam-plecollectionandtesting,weconcludedthatanactivesurveillance programbasedontestingindividualanimalsatsaleyardswasnot practicalandthereforewasnotconsideredfurtherinthisstudy 3.4 Bulkmilktesting
Applicationofbulkmilktesting,reducedthemediantimeto detectionbytwodaysandthenumberoffarmsrequiringcullingby six(p<0.05)comparedtotheBaselinesurveillancestrategy how-everthedurationoftheoutbreakwasnotsignificantlydifferent (p>0.05)(Table7).Therewasnodifferenceintheefficacyofbulk milktestingwhethersamplingwasconducteddaily,everytwodays
oreverythreedays(Table7)
Deployinganintegratedsurveillancesystemwherebulkmilk testingonlywasusedinthedairyingareasandproducereducation
Trang 784 M.G Garner et al / Preventive Veterinary Medicine 128 (2016) 78–86
Table 7
The delay to detection, duration and size of foot and mouth disease outbreaks [median (95% probability interval)] in Victoria, Australia using different surveillance systems.
Saleyard 20 20 (16–42) a 53 (34–99) a 46 (5–310) a
BMT1 18 (9–40) c 46 (14–78) a,b 40 (5–183) c
BMT2 18 (9–40) c 46 (14–76) a,b 43 (5–181) c
BMT3 18 (9–40) c 47 (14–76) a,b 40 (5–178) c
integrated 17 (12–24) b,c 45 (32–76) b 37 (6–176) b,c
* Within each column, figures with the same superscript are not significantly different.
toenhancereportingbypigfarmersinotherareasdidnotprovide
abetteroutcome(p>0.05)thaneitherbulkmilktestingaloneor
producereducationalone(Table7)
4 Discussion
Earlydetectionofdiseaseincursionsisanobjectiveofall
veteri-naryservicesbecauseitresultsinsmalleroutbreaksthatareeasier
tocontrol anderadicate(Carpenteret al.,2011).Achieving
ear-lierdetectionalsohassignificanteconomicbenefitsbecausethe
costsassociatedwithdiseasecontrolwillbelessandlossofexport
earningsduetoexclusionfromFMDsensitivemarketswillalsobe
reduced.Worldwide,recenthistorysuggeststhatoutbreaksofFMD
inpreviouslyfreecountriesaredetectedaboutthreeweeksafter
introductionofthevirustotheindexfarm(Anderson,2002;Bouma
etal.,2003;Yoonetal.,2013);thisisconsistentwiththemodelling
resultsforthecurrentAustraliansurveillancesystempresentedin
thispaper
Wehaveshownthatevenwith100%reportingbyproducers
inthestudyarea,detectionofFMDthroughpassivesurveillance
cannotberealisticallyexpectedearlierthan15daysafter
intro-ductiontotheindexfarmbecauseofthetimedelaysassociated
with:theincubationperiodofthedisease;spreadofthediseaseto
aprevalencewithinaherdtotriggeractionbytheowner,veterinary
investigation,collectionofsamplesandlaboratorytesting.Inour
studyregion,thedifferenceinthedelaytodetectionbetweenthe
currentsurveillancesystemandagoldstandardsystemisonlyfive
dayssothereisonlyasmallwindowforimprovement.Despitethis,
theassociatedreductioninthedurationandextentoftheoutbreak
couldbeassociatedwithsignificanteconomicbenefits
Inthispaper,wehaveconcentratedonthemostlikelypathway
ofentryofFMDintoAustraliai.e.swillfeedingofFMD
contami-natedmaterialtopigs.Whilstotherpathwaysofentryexist,they
areconsideredlesslikely(Matthews,2011;Eastetal.,2013).The
onlyothersignificantpathwayofintroductionintoAustraliaviz
fomitesmayleadtotheinitialintroductionoccurringona
differ-enttypeoffarmhowever,oncetheFMDspreadstoasecondand
subsequentfarms,thepatternofspreadandlikelihoodsof
detec-tionareidentical.Therefore,substantialchangesintheobserved
resultsareunlikely
Improvementsinthetimetodetectioncouldbemade,ifdisease
couldbedetectedinthepre-clinicalphase.Thespecificmethod
ofachievingearlydetectionmustbepracticalandcosteffective
Implementationof activesurveillanceatsaleyards, whilst
theo-reticallyeffective,wouldrequirecollectingandprocessingalarge
numberofsamples(∼700persale)forPCRtestinginrealtime
Evenpre-screeningthesalepopulationwithinfrared
thermogra-phy,assuminganaveragesizedsaleof1350animals,atoneanimal
perminutewouldtake22.5h.Australiahasinternationalairports
atitsgeographicextremitiesandpreservedmeatsmallgoodsand
dairyproduceareroutinelyseizedbyquarantineauthoritiesateach
oftheseairports(confidentialdepartmentreports).Further,
incom-ingpassengersroutinelydispersewidelyandrapidlyfromtheir
pointofarrivaltotheirfinaldestination.Ourpreviouspublication
(Eastetal.,2013)recognisedthisandusedonlythelocationofpig farmsasthemostlikelypointofentryofFMDbecauseanyFMD con-taminatedgoodsneedtobefedtoapigtointroduceFMD.Further,
itisnotunusualinAustralia(EastandForeman,2011;Eastetal., 2014a,b)foranimalstobemovedhundreds(occasionally thou-sands)ofkilometrestoasaleyard.Therefore,anyprogramwould havetofunctionatallsaleyardstobeeffective.Theprogramwould alsoneedtobeon-goingbecausewecannotpredictwhenFMDwill enterAustralia
Inaddition,testinglargenumbersofanimalsevenwithtests withhighspecificitywillinevitablyresultinfalsepositiveresults thatwouldcausemajorlogisticalissuesforsaleyardoperatorsand animalhealthauthoritiesasthefacilitywouldhavetobelocked downuntilthesituationwasresolved
Asimilarconclusionwasreachedwithbulkmilktesting.For earlydetection,BMTtesting wouldalsoneedtobewidespread andongoing.FMDisshedinmilkduringtheincubationperiod
Inexperimentalstudies,Reidetal.(2006)foundthattheearliest periodfordetectionofFMDinmilkwas2–3dayspostinoculation andthatmilkcollectedfromaninfectedcowanddiluted10,000 foldwasabletobedetectedusingtherRT-PCRtests.Theaverage sizeofanAustraliandairyherdis225cowsandtheaverageyield
is17l/cow/day.Thismeansthatthemilkfromfourtofivefarms (900–1125cows)wouldbecombinedintoa20,000lmilktanker.In theearlystagesofinfection,veryfewanimalsinaherdarelikelyto
beinfectedbutifPCRcanreturnapositiveresultaftermilkhasbeen diluted10000fold,testingatthetankerlevelcouldallowdetection
ofoneinfectedcow
Theresultsobtainedwithbulkmilktestingwerevery depen-dentonwheretheoutbreakstarts;largeroutbreaksoccurredin themoreintensiveareas.Themediansizeofoutbreakssizewhen
anincursionstartedinadairyareawastwicethesizeofoutbreaks startinginnon-dairyareas.Whilstbulkmilktestingreducedthe timetodetectionbythreedayscomparedtotheBaseline,when theoutbreakcommencedinadairyarea,thereductionwasonly onedaywhentheoutbreakstartedoutsidethedairyarea(Results notshown).Whilstthesereductionsweresuggestiveofenhanced earlydetection,thedifferenceswerenotstatisticallysignificant
In contrastto ourstudy,Thurmondand Perez (2006) found thatbulkmilktestingprovidedaneffectivemethodofenhancing earlydetectionofFMDinfection.Thisdifferencecanbeexplained becauseThurmondandPerezwereexaminingtheefficacyofbulk milktestingfordetectionofFMDwithinanisolated,infecteddairy herd.Thedesignofourstudyspecificallyrequiresthatinfectionfirst occurswithinasmall-to-mediumpigherdbecausethatisthemost likelypathwayofentryofFMDintoAustralia(Matthews,2011)
Inourscenariotherefore,theinfectionneedstospreadtoadairy farmbeforeitcanbedetectedbybulk-milkscreening.Thedelay
toinfectionofthefirstdairyfarmisafunctionofthegeographic locationoftheinitiallyinfectedpigfarmandthestochastic proba-bilityofspreadofFMDtootherfarms.Thistimedelaytoinfection
ofthefirstdairyfarmcancelsoutanyadvantageofearlydetection providedbybulk-milktesting
Trang 8factoriesinthestudyareawouldrequiretestingof450,000
sam-plesperyear.Althoughlogisticallythiscouldbedone,itwouldbe
expensive.Inaseparatestudywereportaneconomicanalysisof
circumstancesunderwhich BMTiscosteffective(Kompasetal
submitted).Aswithactivesurveillanceatsaleyards,testspecificity
issueswouldbeaconcern.Toinvestigateapositiveresult,all
indi-vidualfarmscontributingtothebulkmilkconsignmentwouldneed
tobefollowedup.Bythetimefollow-uptestingwascompleted,
itislikelythatclinicalsignswouldhaveoccurredontheaffected
farm,negatingmuchofthetimeadvantagefromtheoriginaltest
WhileBMTshowsconsiderablepromiseasanFMDsurveillance
tool,itappearstobebettersuitedtosurveillanceduringan
out-breakandforpost-outbreakproofoffreedomtesting(Kompasetal
submitted)
Weconcludethat,ofthepossibilitiesexaminedinthispaper,
enhancingthepassivesurveillancesystemoffersthebest
opportu-nityforearlydetectionofFMDinVictoria.Thiswillhaveparticular
benefitsinreducingthelikelihoodofgettingalargeoutbreak
Main-tainingahighlevelofawarenessofFMDandpromotingtheneedfor
diseasereportingbyallproducersandthoseinvolvedinlivestock
productionisessential.Ifresourcesarelimited,targetingeducation
programstothosesectorsthatareconsideredtobeatgreaterrisk
ofbeingasourceofintroductionorwherecurrentdiseasereporting
andinvestigationislowislikelytobemosteffective
Acknowledgment
ThisworkwasfundedinpartbytheCentreofExcellencefor
BiosecurityRiskAnalysis
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