2016 Bovine respiratory syncytial virus and bovine coronavirus antibodies in bulk tank milk _ risk factors and spatial a

2016·1.88 MB·English

PreventiveVeterinaryMedicine133(2016)73–83

ContentslistsavailableatScienceDirect
Preventive Veterinary Medicine

journal homepage: www.elsevier.com/locate/prevetmed
Bovine respiratory syncytial virus and bovine coronavirus antibodies

in bulk tank milk – risk factors and spatial analysis

IngridToftakera,∗,JavierSanchezb,MariaStokstada,AneNødtvedta

aDepartmentofProductionAnimalClinicalSciences,FacultyofVeterinaryMedicineandBiosciences,NorwegianUniversityofLifeSciences,P.O.Box8146

Dep,Oslo,Norway
bCen trefo rVeterinaryEpidemiologicalResearch,UniversityofPrinceEdwardIsland,550UniversityAve,Charlottetown,C1A4P3,Canada

a r t i c l e i n f o a b s t r a c t

Articlehistory: Bovinerespiratorysyncytialvirus(BRSV)andbovinecoronavirus(BCoV)areconsideredwidespread
Receiv ed10January2016 among cattleinNo rwayand world wide.T hisc ross-sec tionalstudy wasco nduc tedbasedo nantibody-
AReccceepivteedd i3n S reepvtiseemdb f eorrm20 2196 June 2016 ELISA o f bulk ta nk milk (BTM ) from 134 7 her ds in two neigh borin g cou nties in w estern No rway. The
studyaimsweretodeterminetheseroprevalenceatherdlevel,toevaluateriskfactorsforBRSVand

BCoVseropositivity,andtoassesshowthesefactorswereassociatedwiththespatialdistributionofpos-
Keywords: itiveh erds.Theover allp re valenc eofB RSVa ndBCo Vpos itiveherds inth ere gionw as46.2%and 72 .2%,
BRSV
respectively.Isoplethmapsoftheprevalenceriskdistributionshowedlargedifferencesinprevalence
BCoV
riskacrossthestudyarea,withthehighestprevalenceinthenorthernregion.Commonriskfactorsof
Riskfactors
Sero logy importance for both viruses were herd size, geographic location, and proximity to neighbors. Seroposi-
Spatialscanstatistic tivityforoneviruswasassociatedwithincreasedoddsofseropositivityfortheothervirus.Purchaseof
Dairyc attle livest ock was anad ditio nalriskfac torfo rBCoVser opos itiv ity,includedi nth em odela sin-de gree,whi ch

wasdefinedasthenumberofincomingmovementsfromindividualherds,throughanimalpurchase,over

aperiodoffiveyears.Localdependenceandthecontributionofriskfactorstothiseffectwereassessed

usingtheresidualsfromtwologisticregressionmodelsforeachvirus.Onemodelcontainedonlythex-

andy-coordinatesaspredictors,theotherhadallsignificantpredictorsincluded.Spatialclustersofhigh

valuesofresidualsweredetectedusingthenormalmodelofthespatialscanstatisticandvisualizedon

maps.Adjustingfortheriskfactorsinthefinalmodelshaddifferentimpactonthespatialclustersfor

thetwoviruses:ForBRSVthenumberofclusterswasreducedfromsixtofour,forBCoVthenumber

ofclustersremainedthesame,howeverthelog-likelihoodratioschangednotably.Thisindicatesthat

geographicaldifferencesinproximitytoneighbors,herdsizeandanimalmovementsexplainsomeofthe

spatialclustersofBRSV-andBCoVseropositivity,butfarfromall.Theremaininglocaldependenceinthe

residualsshowthattheantibodystatusofoneherdisinfluencedbytheantibodystatusofitsneighbors,

indicatingtheimportanceofindirecttransmissionandthatincreasedbiosecurityroutinesmightbean

importantpreventivestrategy.

©2016TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBY-NC-ND

license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

1. Introduction bovinerespiratorysyncytialvirus(BRSV)andbovinecoronavirus

(BCoV)areendemicandprevalentinthenationalherd(Gulliksen

TheoverallhealthamongNorwegiandairycattleisgoodwith etal.,2009).Theprevalenceoftheseinfectionsisconsideredhighin

fewendemicinfectiousdiseasespresent.Severalinfections,such mostpartsoftheworld,andtheycausediseaseproblemsleadingto

asbovinetuberculosis,bovinebrucellosisandbovineviraldiarrhea reducedanimalwelfare,increaseduseofantibioticsandfinancial

(BVD),havebeeneliminatedthroughsuccessfulcontrolprograms lossforthefarmer(ValarcherandTaylor,2007;BoileauandKapil,

(Sviland et al., 2015a, 2015b; Åkerstedt et al., 2015). However, 2010; Sacco et al., 2014). BRSV causes respiratory disease, most

ofteninyounganimals,andbronchopneumoniaduetosecondary

bacterialinfectioniscommon(Larsen,2000).BRSVwasthemost

commonlyisolatedagentinrespiratoryoutbreaksincattleherds
∗
Correspondingauthor. inarecentNorwegianstudy(Klemetal.,2014a).BCoVisthecause
E-mail addresse s: [email protected], [email protected] of c alfdiar rhea,respir atory disease a nd winterd ysen ter y(c onta-
(I.Toftaker),[email protected](M.Stokstad),[email protected]
gious diarrhea in adult cattle) (Boileau and Kapil, 2010). Studies
(A. Nødtvedt).
http://dx.doi.org/10.1016/j.prevetmed.2016.09.003
0167-5877/©2016TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBY-NC-NDlicense(http://creativecommons.org/licenses/by-nc-nd/4.

0/).
74 I.Toftakeretal./PreventiveVeterinaryMedicine133(2016)73–83

determineifadjustingforthesefactorschangestheappearanceof

thespatialclusters.

BRSVandBCoVcanbespreadbetweenherdsbydirectanimal

contactandindirecttransmission.Directcontactincludesphysical

contactbetweenanimalsfromdifferentherds,forinstancethrough

sharedpasture,orbyliveanimaltrade.Indirecttransmissionhap-

pensthroughpassivetransferofanimalsecretionsandexcretions

betweenherdsbyfomiteslikeclothingorequipment.

The topography in western Norway, where the area under

investigationislocated,ischaracterizedbymountainsandfjords

separating the herds and limiting direct contact. However, ani-

mal movements between holdings might provide an important

routeoftransmission.In-degreeisameasurementofanimalcontact

which is defined as the number of incoming animal movements

from individual herds, through animal purchase, over a defined

timeperiod(NöremarkandWidgren,2014).Livestockmovements

are often registered in central databases which allows for calcu-

lationofin-degree,butfactorsaffectingindirecttransmissioncan

bemoredifficulttoassessbecauseinformationonmovementof

people and biosecurity routines are not readily available in cen-

tralregistries.Neverthelessmovementofpeopleisassociatedwith

herdsize,becauselargerherdshavemorevisitors(Nöremarketal.,

2013).
The aim of this study was to determine the spatial varia-

tioninherd-levelprevalenceofBRSVandBCoV,asmeasuredby

BTM-antibodies,acrossthestudyregioninwesternNorway.Fur-

thermore,theeffectoftheriskfactorsherdsize,location,animal
Fig.1. Studyarea:MøreogRomsdalandSognogFjordanecountylocatedatthe movemen t, an d pro xim ity to n eighbo rs we re ev aluated a nd the
nort hw estco astof Norwa y.
effect of these risk factors on the spatial distribution of positive

herdswasassessed.

haveshownsignificanteffectsofBCoVinfectiononproductionin

termsofdecreasedmilkyieldandpoorgrowthrate(Tråvénetal.,
2001; Be audeauet al.,20 10b) whic hbo thresult ine conomic lo ss. 2. Materialsandmethods

Bulktankmilk(BTM)serologyisacheapandeffectivemethod
usedto scree nher dsfor infectious d is eases. How ever,due tolong 2.1. Studypopulation

lastingseropositivityafterinfection,aherdwillstaytest-positive
forman yyearsafterc ircula tionofvi ru sint hehe rd(A leniusetal., This cross-sectional study was performed in “Sogn og Fjor-
199 1; Trå vén e t al. , 2001; Kle m et al ., 201 4b). L ikewise, te st- dane” a nd “Møre og R omsda l” co unties on the west coa st of
negati veherd sm ight haveb eenv iru sfre eforyea rsandser ology Norwa y (Fi g. 1). T he region was thought to be a suitab le stu dy
onbulkt ankm ilkist herefo rean indic ator ofh erds tatus withan area bec ause of an e xpected mix of BTM -po sit ive and ne gative
inh eren ttime -lag. herd s. One B TM sam ple from eac h o f 1347 herds was collected
Herd level risk factors previously found to be of importance by the dai ry co mpany (Tine, Norw eg ian D airies SA), between
forBCoV statu sin Swedish dairyherd sareh er dsi ze, notprovid- De cemb er 20 12 and Ju ne 201 3. In 2013, 1854 h erds delivered
ing boots forvis ito rsandge ograp hicloc atio n(Tr åvén eta l.,1999; milk in th e two coun ties, which m eans s ample s were collected
Ohl sonet al., 2010).F orB RSVseropos itivity,h erdleve lri skf actors from 73 % o f all eligible d airy he rds. Mil k sample s wer e treated
foundt ob eof impor tanc eboth inScandinavi aand beyo nda reherd and analy ze d a s descri bed in Sectio n 2.2 , and ea ch he rd was
size,a ge pr ofi leofthehe rd,ty pe ofproducti ona ndexis ten ceof cate gorized a s e ither posit ive or nega tive base d on the B RSV
bord erin gcattle he rds( Norst röme ta l.,2000;Sol ís-Ca lderóneta l., and BCoV ant ibody test resu lts, respectiv ely. If a herd con-
2007;Ohl sonet al.,20 10;Saaeta l., 201 2). tribu ted m ore than one sample d uring the stu dy p eriod, only
Pre viousst ud ies inSca ndin av iah aveindicatedlargevariations the resu lt from the first sample was in clud ed. Pre valence esti-
inprevalenc eofBRS V andBCoVbe tween regions( Elvan der,1996; mat es we re cal culat ed fo r the r egion as a who le and for each
Tr åvén et al., 19 99; B eau deau et al., 20 10a; Kle m et al., 2 013), county separ ately.Truep rev alen cewasc alc ul atedus ingth eRo gan-
butspa tia lan alysesi nvolvingB RSV an dBCoV infecti on sare infre- Gladen -estimator base d on the se nsit ivity and s pecifi city of the
que ntlyrep orted.Fo rcontrol- and erad ication purposes ,lo cating tests as specified by th e m an ufacturer ( Grein er and Ga rd ner,
highand lowrisk area sisimpo rtan tinorderto knowwh ichcon- 2000 ).
trols trat egies sho uldb ea ppliedtod iff erent reg ions. Riskfa ctors During the study period, 98% of all dairy herds were mem-
like herdsize, animal mo vement be tweenher ds,andp roxi mityto bers of th e N orwegi an Dair y He rd Rec ordin g Syste m (N DHRS)
neig hbor sare likelyto varygeogr aphically. Howe ver,i tiscurrent ly whic h p rovi des reliable record s on herd chara cteristics , produc-
notknown ho wgeo gr aphic aldifferencesin riskfacto rs a reassoci- tionpa rameters anddise aseoccu rren ce(Es petvedtetal.,20 13).The
ated witht hesp atialvariatio ninprevale nc eof positiv ehe rdsfor med icalcompan ydi stributi ngtheonly registered BC oV vaccin ein
these two viru ses.Bec ausethe spa tialpattern of antibody -posit ive Norway wasconta ctedtogetin for matio nregardin gthe number of
herds may belarge lydriven by thespa tialpatt er nsofherdcharac- unitssol d.Th euseofthe o nly registeredBR SVvaccine wa srecorde d
teristi cs,su ch asherd sizean dd istan ceton eighbors, sp atial clusters byco ntact ingt he ve terin ary practitione rsby phone. Vete rinarians
ofpositiv ehe rd smig hto nly bereflec tin gthegeog raphica ldistri- ina llmunicipa litie softhestu dyareawithm o rethan 10herdswere
bu tion of k nown charac teris tics . Hence, i t is of major inte rest to co nta cted,covering 12 95 of134 7he rds.
I.Toftakeretal./PreventiveVeterinaryMedicine133(2016)73–83 75

Herds de live ring m ilk in Møre og
Romsdal and Sogn og Fjordane at the
(cid:2)me of sampling
n = 1 854
Did not provide
BTM s ample
n = 5 07 Herds pro viding BTM s amples P REVALENC E ESTIMATES
n = 1347 n = 1347
Herds m issing geographic
coordinates
n = 11
Herds with geographiccoordinates P OINT MAPS, P REVALENC E DENSIT Y
tOhfehseer wdse rwei tthh eg eeoxgclr uaspihoincs c:o ordina tes, n = 1 336 nM =A P1S3 3A6ND INITIAL CLUST ER ANALYSIS:
Not member of NDHRS: n= 134
Not member the en(cid:2)re ye ar of 2 012: n = 1
Incons istent regi st ra(cid:2)ons ANIMALMOVEMENTS AND MULTIVARIABLE
of animal movements: n = 7 Herds with complete regi st ra(cid:2)ons in the ANALYSIS:
NDHRS an d geogr aphic co ordinat es xy-models: n= 1194
n = 1 194 Mul(cid:2)v arIable mode ls: n = 1 194
Re sidual ana lyse s: n = 1 194
In-degr ee: n = 1 194
Fig.2. Flowdiagramofeligible,sampledandanalyzedherds.

2.2. Laboratoryanalysis/outcomevariable cow-years,multipliedbyonehundred.Reportsofrespiratorydis-

easewasavailableattheindividuallevel,andthisinformationwas

BTMsampleswerecollectedbythemilktruckdriversandtrans- dichotomizedtowhetherornottheherdhadoneormoreanimals
porteda tatemp eratu reof4◦C to the dair yplan twere they were withreported re spiratory di sea sed uring the yea ro f2012 .Herds
frozen at b etween −18 an d −2 0◦ C, a nd w ere ke pt at this tem- that were not NDHRS me mbers, o r had i nco mple te registr ations

perature until thawing at the time of laboratory analysis (Tine duringthistime,hadtobeexcludedfromtheriskfactoranalysis,

mastittlaboratoriet in Molde). All BTM samples were analyzed but were still included in prevalence estimates, point maps and
usingindirectELISA (S VANOVIR ® B RSV- abandBC oV-ab ,Svanova isop lethm aps .Forano ver viewofelig ible,sampl edand analy zed

Biotech, Uppsala, Sweden). The optical density (OD) reading of herdsseeFig.2.

450nm was corrected by the subtraction of OD for the negative Data on animal movements between holdings were provided

controlantigen,andpercentpositivity(PP-value)(Takiuchietal., by the Norwegian Food Safety Authority, and in-degree was cal-

2009)wascalculatedas(correctedOD/positivecontrolcorrected culatedasameasureofanimalpurchaseasdescribedinSection
OD)× 100. Thecut-of ffo rapositiv eresultwas setata PP-value 2.4. Acc ess t o recordi ng s on the location of each herd , g iven by

of10forbothtests(Anon.,2016a,b)andthedichotomizedresults geographiccoordinates(latitude,andlongitude,projection:EPSG:
(B RSV +− /and /orBC oV+−) wereuse das the outcomeina llanal- 4326-WGS 84), was pro vided by Tine , Norwegi an Dairies S A. No

yses.ThesensitivityandspecificityoftheELISAsprovidedbythe informationonthelocationofnon-dairycattleholdingswasavail-

manufacturerwere94%and100%forBRSV,and84.6%and100%for able.Asameasureofproximitytoneighbors,themeanEuclidian

BCoVrespectively(Aleniusetal.,1991;Elvanderetal.,1995). distancetothefiveclosestdairyherdswascalculated.Thiscalcu-

lationalsoincludedherdsoutsidethestudyareatoavoidbiased

2.3. Explanatoryvariables valuesforherdsclosetothecountyborders.Thedateatwhichthe
sample wa scolle cted by the tankmi lkdriver ,wa sdivi de dintot wo

Test results were combined with production data and health categories:winter;December1st–March31thvs.summer;April
recordin gs from the NDHRS. A ll sta tistical anal yses wer e done 1st–June30 th.

usingStata/SE(StataCorp.2011.StataStatisticalSoftware:Release

12.CollegeStation,TX:StataCorpLP)unlessotherwisespecified.

Permissiontousethedatabasewasgivenbytheowner,Tine,Nor- 2.4. Animalmovements

wegianDairiesSA.Allrecordingswerefromtheyearof2012.To

describe the general characteristics of the herds in the area the In this study, the term ‘animal movement’ refers to change

mean,standarddeviationandrangewerecalculatedforthefollow- in ownership of an animal. Registration of cattle purchases is

ingherdparametersretrievedfromtablesofannualsummarydata mandatory in Norway. In-degree was used as a measure of live-

intheNDHRS:herdsize,milkproduction,somaticcellcount(SCC), stock movement, and is the number of direct ingoing contacts,

overallherddiseaseincidence,andreplacementrate.Herdsizewas from individual herds, through animal purchase (Nöremark and

definedastheherds’meannumberofcow-yearsin2012(onecow- Widgren, 2014). In-degree was calculated as a sum of purchases

year=365daysforacowinaherd,calculatedforeachcowfrom fromindividualherdsforaperiodofalmostfiveyears;January1st

dateoffirstcalving).SCCwasmeasuredasmeansomaticcellcount 2008–December5th2012.I.e.anin-degreeoffiveforagivenherd

inBMTandmilkproductionwasmeasuredaskgmilkproduced in this study indicates that the herd has purchased live animals

percow-year.Herddiseaseincidencewasthecombinedincidence fromfivedifferentholdingsduringthefiveyearperioddescribed.

rate for all recorded diseases per 100 cow-years in 2012, where Purchases reported after December 5th were excluded from the

recordeddiseasesincludeallcasestreatedbyaveterinarianasthis in-degree calculations because this was the date of collection of

isreportedinon-herdhealthrecordings.Replacementratewasthe the first BTM sample. A total of 347 holdings had not registered

numberofcowsinfirstlactationdividedbytheherds’numberof purchases during this time period. This was assumed to be true
76 I.Toftakeretal./PreventiveVeterinaryMedicine133(2016)73–83

andnoherdswereexcludedduetomissingvalues,butherdswith the receiver operating characteristic (ROC) was used to evaluate

inconsistentduplicateregistrationswereomitted(Fig.2). overallmodelperformance,andtheHosmer-Lemeshowtestwas

usedasatestforthemodelı´sgoodnessoffit,withdatagroupedin

2.5. Riskfactoranalysis tengroupsonthebasisofpercentilesofestimatedprobability.

Pearson and standardized deviance residuals were calculated

2.5.1. Univariableanalyses forbothmodels.Todetectpossibleinfluentialobservations,Q–Q

Atotalof1194outofthe1347sampledherds,or89%,hadcom- plotsofPearsonresidualsweremade,andthedeltabetastatistics

pleterecords,andwereincludedintheriskfactoranalysis.Toassess were calculated. Observations with high residual values or delta

the probability of selection bias the proportion of positive herds betavalueabove0.2wereomitted,andtheanalyseswerererunto

was calculated for the 153 herds (11%) that did not have com- evaluatetheirimpactontheestimates.

pleteNDHRSrecordsaswellasallsampledherds.Herdslacking

geographiccoordinateswereexcludedfromthemapsandspatial 2.6. Spatialpatterns

analyses(Fig.2).

Univariableanalysesforasetof11predictorswereperformedin 2.6.1. Pointmapsandmapsoftheprevalenceriskdistribution

ordertoselectwhichvariablestoincludeinthemultivariablemod- All maps were created using QGIS 2.4.0 (QGIS Development

els. These predictors were chosen from the available data based Team, 2014). Point maps were created to show the point loca-

on a causal diagram and biological plausibility of an association tion of all study herds with respect to their antibody status for

withthedichotomizedtestresultofBRSVandBCoVantibodiesin the two viruses. Kernel density estimation was used for both

BTM.Thesamevariableswereevaluatedforbothviruses.Contin- BRSVandBCoVpositiveherdsinadditiontoallherds,usingthe

uousvariablesassessedforaneffectontheoutcomewere:herd isotropicGaussiankernelfunctionimplementedinthe“spatstat”

size,herddiseaseincidence,averagemilkproductionpercow-year, libraryinR(BaddeleyandTurner,2005).Kerneldensityestimation

replacementrate,meanSCCinBTM,geographiccoordinatesand is a weighted moving average method that can be used to esti-

averagedistancetothefivenearestherds.Thecontinuousvariables matetheintensity,ormeanfunction,forpointprocesses(Berke,

wereincludedassuchintheanalysesunlessotherwisementioned. 2005). The resulting values can be presented as a raster map

Dichotomousvariableswere:timeofsampling(winter;December withonedensityvalueforeachgridcell.Acommonfixedband-

1st–March 31th vs. summer; April 1st–June 30th) and whether widthdeterminedfromthecoordinaterangesfromthestudyherds
ornotthe herd had reported respir atorydise aseth eye arbefore ((1/8) ×min(xrange ,yrang e))w asused.Di viding thera nge distan ceby

sampling.Theassociationbetweenin-degreeandtheoutcomewas eightwasdonetoavoidoversmoothingtheintensityfunction,as

assessedtreatingin-degreebothasacontinuous-andasacategor- reportedelsewhere(Vandersticheletal.,2015).Generatingarisk

icalvariable.Foranalyticalandinterpretationalreasonsin-degree mapwithspatialpointdata(locationsofcasesandnon-cases)is

waseventuallyincludedasacategoricalvariablewiththreecat- basedontheratiooftwointensitiesasdescribedbyBerke(2005).

egories:category1for0–1directingoingcontacts,category2for Thus, the isopleth map showing prevalence risk on a smoothed

2–9directingoingcontactsandcategory3formorethan9direct colorscalewasmadebydividingtheKerneldensityrasterlayer

ingoingcontacts. forthecasesbytheKerneldensityrasterlayerforthebackground

Forallvariablestheassociationwiththeoutcomewasevalu- population.

ated by simple logistic regression (Wald-test), and the predictor

wasincludedinthesubsequentmodel-buildingprocessifthep- 2.6.2. Localclusters

value<0.2. Thespatialscanstatistictestwasappliedtoexplorespatialclus-

Linearity of continuous predictors was assessed by grouping tersofpositiveherdsbyusingthesoftwareSaTScanversion8.1.1

observationsingroupsofequalsize,andmakingplotsofthegroup (Kulldorff,2009).Thespatialscanstatisticcananalyzespatialpoint

meansagainstthelogoddsoftheoutcome.Incaseofnon-linearity, data(KulldorffandNagarwalla,1995;Kulldorff,1997),andcluster

differenttransformationswereevaluated.Toavoidmulticollinear- detectionisdonebygraduallyscanningawindowacrossspace,not-

ityinthemodel,correlationcoefficientsbetweenallpairsoftwo ingthenumberofobservedandexpectedobservationsinsidethe

predictorswerecalculatedbeforethemultivariableanalysiswas windowateachlocation(Kulldorff,2015).Clustersofpositiveherds

performed(Dohooetal.,2003). weredetectedusingtheBernoullimodelwithanalysissettingsas

purely spatial, scanning for areas with high rates and maximum

2.5.2. Multivariableanalyses spatialclustersize20%ofpopulationatrisk.Nooverlapofclusters

Based upon the significant associations from the univariable wasallowed.Resultsfromtheanalysesincludeslocationofclus-

analyses,twologisticregressionmodelswithdifferentoutcomes ters,thevalueofobserved/expectedcases,therelativeprevalence

werebuilt:onewiththeBRSVantibodystatusoftheherdasthe (notshown)andap-valueforeachclusterobtainedbytheMonte

outcomeandthesecondwithBCoVantibodystatusastheoutcome. Carlomethod(999iterations).

Largescaletrends,alsocalledfirst-orderspatialeffects,relateto Toevaluatespatialclustersofpositiveherdsfirstaftercorrecting

variationinthemeanvalueofaspatialprocess(Dohooetal.,2003), forfirstordereffectsandthenafteradjustingforotherherdlevel

andtocontrolforpossiblefirst-ordereffectsthex-coordinate(lon- riskfactors,twosetsoflogisticregressionmodelswerebuiltusing

gitude) and y-coordinate (latitude) were added in the model as BRSV-andBCoV-testresults(0/1)astheoutcome.Onesetincluded

continuous variables. Biologically plausible pairwise interactions only the x- (longitude) and y- (latitude) coordinates (called the

betweensignificantvariablesfromthefinalmodelswereassessed xy-models). The other set also included the predictors of inter-

byaddingtheircross-productinthemodelandthendetermining estthatremainedinthemodelasdescribedinsection2.5.2.After

ifthecoefficientforthetermwasstatisticallysignificant.Forinter- modeldiagnosticsandevaluationofmodelfit,thedevianceresid-

actions, a more stringent criterion was used for model inclusion uals from all four models were obtained and analyzed using the

(p<0.02)inordertochoosethemostparsimoniousmodel.Possible spatialscantestunderthenormalprobabilitymodelwithanalysis

confoundingfactorswereidentifiedthroughacausaldiagramand settings as purely spatial, scanning for areas with high values of

monitoredbycalculatingthechangesinothercovariateswhenone residuals,andmaximumspatialclustersize20%ofpopulationat

factorwasaddedandwithdrawnfromthemodel.Thefinalmodels risk. No overlap of clusters was allowed. The output reports key

werefittedusingamanualbackwardstepwiseprocedure,witha statistics, including the location, the number of herds, the log-

selectionthresholdofp<0.05.Theareaunderthecurve(AUC)of likelihood ratio and a p-value for each cluster obtained by the
I.Toftakeretal./PreventiveVeterinaryMedicine133(2016)73–83 77

Table1

Mean,standarddeviation(STD)andrangeforherdparametersobtainedfromNDHRSfromtheyear2012in1194dairyherds,includedinastudyofBRSVandBCoVas

measuredbybulktankmilkantibodiesinthestudyareaofSognogFjordaneandMøreogRomsdalcountyonthenorthwestcoastofNorway.

Variable Mean Overallmean STD Range

BRSV+ BRSV− BCoV+ BCoV−

Herdsize 25.8 16.8 23.3 14.9 20.9 14.7 3.3–123.6

Averagemilkproductionpercow-year,inkg 7295 7161 7306 7012 7222 1123 2984–13682

MeansomaticcellcountinBTM 122.8 116.0 121.3 113.0 119.1 40.4 24–273

Meandistancetothe5nearestherds,inkm 1.8 2.3 1.9 2.6 2.1 1.7 0.19–18.0

Replacementrate 41.9 42.2 42.9 40.0 42.0 16.9 0–128(IQR:31–51)
Herddisease incid ence* 94.0 91.4 95.2 86.0 93 66.9 0–500
In-de gree** 2 2 2 1 2 9.7 0–181

* Herddiseaseincidenceper100cow-years(year2012).
** In-de gree:me diannum ber ofdi rectingoin gcont actsthroughanimalpurchaseoveraperiodofalmostfiveyears.

MonteCarlomethod(999iterations).Becausethesamemodelling 3.2. Animalmovements

approachwasusedforthespatialassessmentoftheresidualsfrom

boththexy-andthefinalmodelitwaspossibletocomparethe Incominganimalmovementswereregisteredfrommostparts

spatialclustersofresidualsbeforeandaftercorrectingfortherisk of the country, but the majority of purchases were across short

factors. distanceswithinthestudyregion.Forthe1194herdsthathadcom-

pleterecords,themedianin-degreeovertheperiodofalmostfive

years(January1st2008–December5th2012)was2–witharange

3. Results of0–181.

3.1. Studypopulation 3.3. Multivariablemodel

Mean values, standard deviations and ranges of descriptive Timeofyearforsamplingwasexcludedfromthemodeldueto
paramete rsforth estudyp opulationar epre sented in Table1.The collinear ity with th e geograp hic coordinat es (r= −0 .79 for x an d
overallappa ren tpr evalen ceofseropo siti veherdsin th estud ya rea r=−0.81 fo r y). The x- and y-c oordinates w er e also corr el ated

was46.2%forBRSV,and72.2%forBCoV.40.7%ofallherdswere (r=0.71),whichwasexpectedduetothenorth-eastslopeofthe

positiveforbothvirusesand22.3%werenegativeforbothviruses coastline. Because no herds are located off-shore, an increase in

onBTM.Thismeansthataherdwhichisantibodypositiveforone ywilltendtoentailanincreaseinx.Thestabilityofthemodels

virushada5.3timesincreasedoddsofpositivityfortheothervirus. wastestedbyremovingthecoordinatesoneatatime,fittingthe

Theprevalenceofpositiveherdswashigherinthenortherncounty modelwithonlythex-coordinate,onlythey-coordinateandboth.

(MøreogRomsdal),54.4%forBRSVand79.8%forBCoV,compared Nosubstantialchangeswereobservedintheestimatesfortheother

tothesoutherncounty(SognogFjordane),wheretheprevalence covariatesinthemodel,anditwasdecidedtokeepbothcoordi-

ofBTMpositiveherdswas36.7%forBRSVand63.4%forBCoV. natesdespitethecorrelationinordertocorrectforlargegeographic

BasedonthesensitivityandspecificityoftheELISAtestsgiven trends(firstordereffects)sothatanyremaininggeographicvaria-

bythemanufacturer,thecalculatedtrueprevalencewas49.1%for tionintheresidualscouldbeattributedtolocaldependence.The

BRSVand85.3%forBCoV.Forthe153herds(11%)thatprovided distancetothefiveclosestdairyherdsshowedlackoflinearitywith

milksamplesbutwerenotpartofthemultivariableanalyses(see thelogoddsoftheoutcome,andwasthereforelogtransformed

Fig. 2), the prevalence was 50.3% and 77.1% for BRSV and BCoV, (naturallogarithm).

respectively.
Vaccination against BRSV was known to have been used in a 3.3.1. BRSV-model

totalofsixherdsbeforethetimeofsampling.Fiveofthesewhere VariablesincludedinthefinalBRSVlogisticregressionmodel

inthenortherncounty(MøreogRomsdal)andoneinthesouth- were:herdsize,x-andy-coordinatesandlogofmeandistanceto

erncounty(SognogFjordane).Itwasdecidednottoexcludeany thefiveclosestdairyherds(inkm).ResultsfromtheBRSVlogistic

herdsduetovaccinationbecausevaccinationwassorarelyused regression model are shown in Table 2. The area under the ROC

andbecausetheherdsthathaduseditreportedaprolongedhis- curvewas0.73,andthep-valueoftheHosmer-Lemeshowgoodness

toryofrespiratorydiseaseandwerelikelytobeantibodypositive offittestwithtengroupswas0.91indicatingacceptableoverallfit

onBTMsamplingregardlessoftheuseofvaccine.Regardingthe of the model. Calculation of the delta beta statistics revealed no

BCoV vaccine, no units of the vaccine were sold to pharmacies obviousoutliersandnoobservationshaddeltabeta>0.2.

in the study area during 2012. This is not a guarantee that it

is not used, but strongly implies limited use, and thus the risk 3.3.2. BCoV-model
th at u se of vacc ine woul d influen ce the resul ts w as co nsid ered Va riablesincludedinthefinalBCoVlogisticregressionmodel
negl igibl e. were:herds ize,herd dis ease incid ence, x-and y-coordinat es,log

Table2

Estimatedoddsratioswith95%CIandcoefficientswithstandarderrors,alongwithp-valuesbasedonalogisticregressionmodelonfactorsassociatedwithherdlevel

BRSV-statusasmeasuredbyantibodiesinbulktankmilkin1194dairyherdsintwocountiesonthewest-coastofNorway.

Variable OR 95%CI Coefficient Std.Error P-value

Herdsize 1.05 (1.04–1.06) 0.046 0.006 <0.01
x-coo rdin ate(longitude) 0.60 (0.49–0.72) −0.53 0.01 <0.01

y-coordinate(latitude) 3.55 (2.58–4.90) 1.27 0.16 <0.01
Logofmeand istanceto 5nearestherds,inkm 0.53 (0.44–0.64) −0.6 3 0.09 <0.01
Con sta nt – −76.0 8 9.66 <0.01
78 I.Toftakeretal./PreventiveVeterinaryMedicine133(2016)73–83

Table3

Estimatedoddsratioswith95%CIandcoefficientswithstandarderrors,alongwithp-valuesbasedonalogisticregressionmodelonfactorsassociatedwithherdlevel

BCoV-statusasmeasuredbyantibodiesinbulktankmilkin1194dairyherdsintwocountiesonthewest-coastofNorway.

Variable OR 95%CI Coefficient Std.Error p-value

Herdsize 1.05 (1.03–1.07) 0.052 0.009 <0.01
Herd dise aseincidence* 1.003 (1.001–1.00 5) 0.003 0.001 <0.01
x-coo rdinate (longitude) 0.78 (0.63–0.95) −0.25 0.11 0.017

y-coordinate(latitude) 3.54 (2.53–4.95) 1.26 0.17 <0.01
Logofmeand istanceto 5nearestherds,inkm 0.46 (0.37–0.56) −0.7 8 −0.7 8 <0.01
Ind egr ee**,c ategory1 1,re ference

Indegree,category2 1.73 (1.28–2.34) 0.53 0.15 <0.01

Indegree,category3 5.97 (2.94–12.10) 1.80 0.36 <0.01
Co nstant – −77. 02 10.1 2 <0.01

* Herddiseaseincidenceper100cow-years(year2012).
** Then umbero faherd’s dire ctin goingcont actsth roughanimalpurchasefromuniqueherdsoveraperiodforalmostfiveyears.Category1includesherdswithin-degree

0–1,category2forin-degree2–9andcategory3forin-degreemorethan9.

Fig.3. Pointmapshowingthelocationof1336dairyherdsinthestudyareaatthenorthwestcoastofNorway.Herdswereclassifiedbasedonantibody-ELISAofonebulk

tankmilksamplecollectedduringtheperiodDecember2012toJune2013,andpositiveherdsaremarkedasreddotswhereasnegativeherdsaremarkedasbluetriangles.

MapAshowsBRSVantibodystatusandMapBshowsBCoVantibodystatus.

ofthedistancetothefiveclosestdairyherdsandin-degree.After ing spatial variation of positive herds for the two viruses. These

theintroductionofin-degreethevariables“replacementrate”and mapsshowthedensityofpositiveherdsoverandabovetheden-

“reportedrespiratorydisease”werenolongerpositivelyassociated sityofthebackgroundpopulation,andareshowninFigs.4and5.

withBTMpositivity.Resultsfromthelogisticregressionmodelare Thespatialdistributionofriskissimilarforthetwoviruseswiththe

shown in Table 3. The BCoV model had an area under the ROC highestprevalenceriskinthenorthwesternregion,andthelowest

curveof0.81,andaHosmer-Lemeshowgoodnessoffittestwith prevalenceriskinthesouth.

tengroupsgaveap-valueof0.63,indicatinggoodoverallfitofthe

model.Calculationofthedeltabetastatisticdetectedfivepossible 3.4.2. Localclusters
influen tialobserva tio ns(d eltab eta> 0.2).Ho wever,om itti ngthese Ap plicat ionofthespatialscantestundertheBernoullimodel
didnotsub stantiallyinfl uence them odel estimates. Themode lhad identifiedfives pa tial clusters ofB RSV- positiv e,a ndfourof BCoV-
low est predictiveab ilityforla rge BCoVn egativehe rds, witha rel- positiveh erds (p<0.0 5).TheB RS V-positiveclus ters inclu de dfrom
atively shortdista nceto the fiven earest dairyhe rds,loc ated in the 15to18 2herd s an dthe rati oofobserved/ expected casesra nged
norther ncou nty.Thes eh erd swe reBCoV -nega tivede spiteth eh igh fro m 1.91 to 2.1 7. Fo r cl uster s o f BCoV-positive her ds th e num-
probabili tyofap ositive outco mep redictedbythe model. ber o f her ds in a c lust er range d f rom 30 to 160 and th e ra tio of

observed/expectedcasesrangedfrom1.23–1.39.

3.4. Spatialpatterns Thelocationofspatialclustersofhighvaluesofdevianceresidu-

alsfromthexy-modelsandthefinalmodelsareshowninFig.6.Key

3.4.1. Pointmapsandmapsofprevalenceriskdistribution statisticsfromtheanalysesareshowninTable4.Aspatialclusterof

ThepointlocationofallstudyherdsareshowninFig.3.Ker- highvaluesofresidualsisanareawithanexcessofcasesbasedon

nel density estimation was used to make smoothed maps of the whatisexpectedunderthecurrentmodel.Forthexy-modelsclus-

prevalenceriskdistributionforevaluationoflargetrendsregard- teranalysisusingthespatialscantestidentifiedseveralareaswith
I.Toftakeretal./PreventiveVeterinaryMedicine133(2016)73–83 79

Table4

Keystatisticsfromtheclusteranalysesofresidualsfromthelogisticregressionmodelwithx-andy-coordinatesastheonlypredictors,andthefinallogisticregressionmodel

withallriskfactorsincluded,forBRSVandBCoVantibodiesinbulktankmilkin1194dairyherdsintwocountiesonthenorthwestcoastofNorway.“Meaninside”and“Mean

outside”referstothemeanvalueofdevianceresidualsinsideandoutsidethecluster,respectively.

Numberofcases Meaninside Meanoutside Standarddev. Log-likelihoodratio p-value

BRSVxy-model:
1.clu ster 180 0.66 −0.15 1.11 39.92 0.001
2. cluster 41 1.21 −0.072 1.12 25.08 0.001
3. cluster 31 1.08 −0.057 1.13 15.13 0.001
4. cluster 16 1.38 −0.047 1.14 12.30 0.005
5. cluster 10 1.55 −0.041 1.14 9.64 0.040
6. cluster 30 0.86 −0.051 1.14 9.38 0.044

BRSVfinalmodel:
1.clu ster 180 0.58 −0.13 1.06 33.32 0.001
2. cluster 41 0.90 −0.060 1.08 15.51 0.001
3. cluster 31 0.96 −0.053 1.17 13.22 0.003
4. cluster 16 1.25 −0.044 1.08 11.27 0.009

BCoVxy-model:

1.cluster 160 0.64 0.047 1.03 22.15 0.001

2.cluster 52 0.86 0.092 1.04 13.52 0.001

3.cluster 233 0.43 0.052 1.04 12.47 0.001

4.cluster 72 0.69 0.090 1.04 11.31 0.003

BCoVfinalmodel*:

1.cluster 72 0.69 0.067 0.96 13.86 0.001

2.cluster 37 0.88 0.080 0.96 12.46 0.001

3.cluster 122 0.50 0.060 0.96 11.44 0.003

4.cluster 233 0.34 0.048 0.96 8.32 0.027

* NotethatforBCoVtheorderoftheclustersarenotthesamefromthetwomodelsbecauseofchangeinlog-likelihoodratio.The1.clusterfromthefinalmodelis

equivalent(regardinglocation)tothe4.clusterfromthexy-model.

Fig.4. IsoplethmapoftheprevalenceriskdistributionofBRSV-positivitybasedon Fig.5. IsoplethmapoftheprevalenceriskdistributionofBCoV-positivitybasedon

classificationofherdsbyantibodyELISAonbulktankmilk.Sampleswerecollected classificationofherdsbyantibodyELISAonbulktankmilk.Sampleswerecollected

duringtheperiodDecember2012–June2013,and551outof1336dairyherdswere duringtheperiodDecember2012–June2013,and863outof1336dairyherdswere

BRSVantibodypositive. BCoVantibodypositive.

highvaluesofdevianceresiduals.Theseclustersconsistofpositive dal and the other three in Sogn og Fjordane. The most northern

herdswithalowprobabilityofpositivitypredictedbythemodel, clusterhadapproximatelythesamegeographiclocationforboth

i.e. the herds were expected to be negative when correcting for viruses,apeninsulainthenorthwestofMøreogRomsdal(Romsdal-

large(firstorder)geographictrends.Clusterswithap-value>0.05 shalvøya).Forthefinalmodelsthedevianceresidualswerespatially

wereexcluded.Theclusteranalysesofmodelresidualsdetectedsix clusteredinfourlocationsforbothviruses(p<0.05,Fig.6).Forthe

spatialclustersofBRSV-positive,andfourofBCoV-positiveherds. BRSV-modelthenumberofclusterswasreduced,butthechanges

TheBRSV-positiveclustersincludedfrom10to180herds,twoclus- in log-likelihood ratio of the remaining clusters were small. For

terswerelocatedinMøreogRomsdal,oneontheborderbetween BCoVthenumberofclustersremainedthesame,buttherewere

thetwocounties,andthreewerelocatedinSognogFjordane.For substantialchangesinthelog-likelihoodratio,seeTable4.

clustersofBCoV-positiveherdsthenumberofherdsinacluster Thespatialscanstatisticwillsearchforclusterswithhighvalues

rangedfrom52to233,oneclusterwaslocatedinMøreogRoms- ofresiduals,andwhatisconsideredhighvaluesisrelativetothe
80 I.Toftakeretal./PreventiveVeterinaryMedicine133(2016)73–83

Fig.6. GeographicmapofthestudyareaindicatingthelocationofclustersofhighvaluesofdevianceresidualsfromtheBRSV(AandB)andBCoV(CandD)logisticregression

models.Clustersfromxy-modelsareshowninAandC,andspatialclustersofhighvaluesofdevianceresidualsaftercorrectingforalltheriskfactorsinthefinallogistic

regressionmodelsaredepictedinBandD.Analyseswereperformedforn=1194herdsinthestudyareasituatedinthenorthwestpartofNorway.Clustersweredetected

usingthenormalprobabilitymodelofthespatialscanstatistic,andallclustershaveap-value<0.05.Clustersaresortedaccordingtolikelihoodratio,withthemostlikely

clusterasnumberone(numberdisplayedinthecenter).

rest.ThereferencevalueswasdifferentfortheBRSVandtheBCoV differencesbetweenstudyregions.Thestudyregionwasselected

modelsbecausetheBRSVmodelshadhighervaluesofresidualson asitwasbelieveditwouldcontainamixofBTMpositiveandneg-

averagebothforthexy-modelandforthefinalmodel.Thismeans ativeherds.Thelargevariationinprevalenceacrossregionsisin

thattheevaluationofspatialclustersmustbeinterpretedasclus- agreementwithastudyperformedbyKlemetal.(2013).

tersofunexplainedvariationintheoutcomeforthatmodel,and ForbothmodelstheoddsofbeingBTMpositiveincreasedfrom

comparisonofthespatialclustersofBRSVpositiveherdsandBCoV south to north (latitude) and for BRSV from east to west (longi-

positiveherdsmustbedonewithcaution. tude).Theselargetrendscanbeinterpretedasfirstordereffects,

butbecausethetimeofsamplecollectionwascorrelatedwiththe

4. Discussion geographiccoordinates,andhadtobeomittedfromthemodel,the

observedgeographictrendscannotwithcompletecertaintybesep-

The overall apparent prevalence of seropositive herds in the aratedfromapossibletemporaleffect.About40%oftheherdswere

studyareawas46.2%forBRSVand72.2%forBCoV,whichislow positiveagainstbothBRSVandBCoV,andtheoddsofbeingpos-

comparedtoreportsworldwide(Patonetal.,1998;Uttenthaletal., itiveforoneviruswereapproximatelyfivetimeslargerifaherd

2000;Ohlsonetal.,2010).Thisisalsolowerthanestimatesfrom waspositivefortheothervirus.Thelargeproportionherdswith

previous studies in Norway using serologic methods (Gulliksen antibodies against both viruses was not surprising given known

etal.,2009;Klemetal.,2013).Thepresentstudyclassifiedherds commonriskfactors.

according to detection of antibodies measured in a milk sample Herdsizewaspositivelyassociatedwithseropositivityforboth

taken from the BTM. This methodology generally increases the BRSVandBCoV.Increasingtheherdsizebyonecow-yearincreased

prevalenceofadiseasewhencomparedtoindividualsamplingofa theestimatedoddsofbeingantibodypositiveby5%forbothviruses.

groupofyounganimals–themethodusedbythepreviousNorwe- Thiscorrespondstoa72%and84%increaseintheoddsofBTMpos-

gianstudies.Hence,itmakesthediscrepancybetweenthepresent itivitywhenincreasingtheherdsizeacrosstheinterquartilerange

studyandthepreviousonesevenlarger,andismostlikelydueto forBRSVandBCoV,respectively.Theassociationbetweenherdsize
I.Toftakeretal./PreventiveVeterinaryMedicine133(2016)73–83 81

andBRSVandBCoVpositivityiswelldocumented(Tråvénetal., of risk factors included in the logistic regression model, such as

1999; Norström et al., 2000; Solís-Calderón et al., 2007; Ohlson proximitytoneighbors,herdsizeandlargegeographictrends(x-

etal.,2010).ThedairyproductioninNorwayistypicallyorganized andy-coordinates).However,spatialclustersofhighresidualval-

in small units with a mean of 24.2 cow-years per herd in 2013 ues from the final models indicates that there are still spatially

(Anon.,2015).Eventhoughthisissmallerthaninmostdeveloped dependent unmeasured risk factors. No information on biosecu-

countries this association holds true. The reason for the associa- ritywasavailableandgoodhygieneandhusbandrypracticescould

tion remains unclear; however, it may be linked to larger herds beanunmeasuredpreventivefactor.AstudybyOhlsonetal.(2010)

having more indirect contact for instance via visits from veteri- showedapreventiveeffectofusingbootcoversonBCoVpositivity.

narians, AI technicians, advisory personnel or others (Norström, Othernon-measuredpotentialriskfactorsthatcouldbespatially

2001).Furthermore,herdsizemightbeassociatedwithdifferences dependentincludetheuseofcommongrazing,andhistoricaldata

inmanagement,andlargerherdsmightprovidebetterconditions onpreviousdiseaseoutbreaks.Bothwinterdysenteryandrespi-

forintra-herdviruscirculation. ratory disease typically occur as epidemics with years between

Itisinterestingthatin-degreewasonlyasignificantpredictor (BoileauandKapil,2010).Anepidemicspreadoftheseviralinfec-

intheBCoVmodel,andnotforBRSV.Forthestudypopulation,the tions might cause all, or the majority of, herds in an area to be

majorityofpurchasedlivestockcamefromwithintheregion,and antibodypositive,andthusaffectthespatialdistributionofpositive

thefairlylowherdlevelprevalenceofBRSVinthisregioncould herdsforyears.

explain why the number of ingoing contacts (in-degree) was not ForBCoVthenumberofclustersremainedthesameaftercor-

associated with BRSV positivity. The most commonly purchased rectingfortheriskfactorsinthefinalmodel,howeverwithlarge

animalsarecalvesandyoung-stock,andbecausetheprevalence changesinthelikelihoodratio.Thesechangesinthelog-likelihood

oncalflevelislowerthanonherdlevel,theriskofbuyingayoung ratiomeanthatadjustingforgeographicdifferencesinherdsize,

animalwitheithercurrentviralinfectionorantibodiesmightnotbe proximitytoneighborsandin-degreeresultsinamorerandomdis-

highenoughtoshowanassociationwiththeoutcome.Thepreva- tributionoftheresiduals.However,theeffectwasnotuniformfor

lenceofBCoVishigher,andthustheriskofbuyingantibodypositive allclusters,indicatingthattheeffectoftheriskfactorsmightnot

or infected animals is also higher, and more likely to affect the bethesameinallareas.ComparedtotheBRSV-model,themod-

BTMresult.Abiologicalexplanationbehinddifferencesinthelike- eratevaluesofobserved/expectedfortheBCoVclustersfromthe

lihoodofdirecttransmissionbetweenthetwovirusesshouldalso Bernoullimodelalsosupportthatlocaldependencemightbemore

beconsidered.Animportantdifferenceinthepathogenesisofthe importantforBRSVthanforBCoV.ThespatialclustersofBRSVanti-

twovirusesisthatBCoVreplicatesbothincellsintherespiratory body positive herds had high values of observed/expected from

tractandintestinalepithelialcells,leadingtosheddingofvirusin the Bernoulli model, and there were relatively small changes in

nasalsecretionsaswellasinfeces(BoileauandKapil,2010).On log-likelihoodratiooftheclustersbetweenthexy-andthefinal

theotherhand,BRSVonlyreplicatesincellsoftherespiratorytract model, which might indicate strong local dependence. This also

(ValarcherandTaylor,2007).However,severalimportantaspects agreeswiththelowerpredictiveabilityofthismodelcomparedto

of the pathogenesis are common for the two viruses: Shedding theBCoVmodel(AUCvalues0.73and0.81,respectively).ForBRSV

ofvirusishighestintheacutestageoftheinfectionanddisease theresultsimplytheexistenceofspatiallydependentunmeasured

canvaryfromsubclinicaltosevere(Larsen,2000;Choetal.,2001; riskfactorsandthateachherdreliesstronglyonthestatusofits

BoileauandKapil,2010). neighbors,thusindicatingtheimportanceofindirecttransmission

Increasingmeandistancetothe5nearestdairyherdswasasso- routes. The implementation of a high level of biosecurity could,

ciated with a significant decrease in odds of BTM positivity for therefore,beimportanttopreventvirusintroduction.Thehigher

bothviruses.Associationbetweenexistenceofborderingherdsand overallpredictiveabilityoftheBCoVmodelcomparedtotheBRSV

BRSVwasalsofoundbySaaetal.(2012).Anotherstudyfoundthat modelmeansthatdespiteahigheroverallprevalenceofBCoVit

theoddsofBCoVpositivitydecreasedasthedistancetothenear- iseasiertopredicttheserologicstatusofaherd,ortolocate“high

estcattleherdincreased,butnoassociationwasfoundforBRSV riskherds”,forBCoVthanforBRSV,basedonthenumberofanimals

(Ohlsonetal.,2010).Norström(2001)foundanincreasedriskof purchasedandrelativelyconstantfactorslikeherdsize,proximity

outbreakofBRSVifatleastonepositiveherdwaswithinaradius toneighborsandlocation.Thedifficultyinfindingstrongassocia-

of 500m of a herd. BRSV and BCoV are enveloped viruses, with tionsbetweentheinvestigatedriskfactorsandBRSVpositivity,and

relativelyshortsurvivaltimeoutsidethehost,dependingonenvi- thestronglocaldependence,couldmeanthatthespreadofBRSVin

ronmental factors such as temperature, humidity and light (Hall thisregionhasbeenofamoreepidemiccharacter,involvingmore

etal.,1980;Larsen,2000;Wolffetal.,2005;Casanovaetal.,2010). stochasticitythanwhathasbeenthecaseforBCoV.

As the number of infective virions on equipment decreases over ClassificationofherdsinthisstudywasbasedonasingleBTM

time,thelikelihoodofindirecttransmissionbyfomitesdecreases sample. The use of BTM serology cannot be relied on to give an

withincreasingtravellingtimeandthereforedistance.Distanceto updatedpictureoftheinfectionstatusofaherdbecauseanimals

neighbors will also influence on the number of possible indirect shedantibodiesforyearsafterinfection(Aleniusetal.,1991;Tråvén

contactsforaherd,andthusthelikelihoodofexposure.Thiseffect etal.,2001;Klemetal.,2014b).Theproportionofherdswithongo-

mightbemoreevidentduringperiodsofhighinfectiouspressure ingorrecentinfectionisthereforelikelytobemuchlowerthanthe

(epidemics).Itisalsopossiblethatthedistancebetweenherdsis prevalenceofBTM-positiveherds.Severalotherdiagnosticoptions

associatedwiththeriskofdirecttransmission,ifanimalsinherd for classification of herds with respect to BRSV and BCoV status

dense areas have more contact during pasture time in the sum- exists.Serologyofindividualanimals,eitherusingmilkorblood

mer.However,wedidnothaveanyinformationonthelocationof samples, can give a more recent picture of the herds’ infection

pastures. historythanBTMsamples,dependingontheageandnumberof

Theresultsofthisstudyshowthatthegeographicdistribution animalssampled.(Ohlsonetal.,2009;Klemetal.,2013).Theideal

of BRSV and BCoV in the study area are far from uniform, and methodforclassifyingherdswithrespecttodetectingviruscircu-

thattherearebothlocalhighriskclusters(Fig.6),andlargegeo- lationwouldbetodetectthevirus;however,thisisdemandingon

graphictrends(Figs.4and5).Theclusteranalysesontheresiduals alargerscale(Klemetal.,2013).

showedthatsomeofthelocaldependencechangedwhencorrect- TheantibodyELISAtestsusedtoclassifyherdsaseitherpositive

ingforotherriskfactors.Inotherwords,localdependenceseems or negative for either virus are imperfect. This means that there

to be partially explained by spatial variation in the distribution willbesomemisclassificationofoutcome,whichcouldleadtoan
82 I.Toftakeretal./PreventiveVeterinaryMedicine133(2016)73–83

underestimationofprevalence.(Estimatesoftrueprevalenceare ofNorway(NFR-projectNo224771/E40),TheNorwegianResearch

showninSection3.1).However,aspreviouslymentioned,preva- Funding for Agriculture and Food Industry and TINE Norwegian

lence estimates based on bulk tank milk serology will be much DairiesSA.

higherthantheproportionofherdsthathavecirculatingvirus,so

comparedtothistheinaccuracyintroducedbyanimperfecttestis

negligible.Whenevaluatingtheeffectoftheriskfactors,misclas-
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stru ct ures in the data may be more c omplex th an a sim ple latitu- Berk1e7, 3O–.,1 28020,5h.t tEpx:p//ldorxa.dtoori.yo rsgp/a1t0ia.1l 0re1l6a/tji.vper ervisekt mmeadp.p2i0n0g5. .P0r7e.v0.0 V3e.t. Med. 71,
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aunndli ktehley itnhcalutstihoen soigf nthifiec axn- caendo ryd-ciroeocrtdioinnaotefst hine tehfefe mctoedsetilms, aitt eiss Cho,EKn.vOir.,oHna. sMoikcs ruozb,iMo l.. ,7N6i,e 2ls7 e1n2,–P2.R7.1,7C,h hatnt gp,:/K/d.Ox..,dLoait.horr go/p1,0S..1,1S2a i8f,/a Le.Jm.,2.0020219. 1-09.
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smeanntaatgievme efonrt tshyest eNmorswfoergidaani rdyapirryo dhuecrtdio ans aar ewchoomlep,a braebcaleusaec rtohses Dohdoeot,eI.cRt.i,oMn.a Artricnh,.W Vi.r,oSlt.r 1 y4h6n,, 2H4.,0 210– 0234.1V9e. terin aryEpid em iologic Rese arch .AVC
thecountry.T heexter nal valid ityistheref ore deemedgoo d,and Inc. ,Cha rlotteto wn ,Prince Edw ardIs land,Cana da.
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the results might also be valid for other temperate areas of smaller- ofan indi rectELISA fo rthedete cti onofa nti bodies toboviner espi ratory
scaledairyproduction. sy ncy tialviru sinm ilk, bulk milk,and se rum.J.Vet .D iagn.In vest.7,
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to prev ent betw een -herd transm ission of v irus. leexv peol sou fr aenitnibtohdeihese ridn . bVueltk. Rtaenc k. 1m7 i5l,k4 a7n,dh tbt opv:/i/n dex r.desopi.io rragt/o1r0y. 1sy1n3c6y/ vtira.1l v0i2r4u0s 3.
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