Lying in wait: the resurgence of dengue virus after the Zika … · 2020. 8. 10. · Lying in wait: the resurgence of dengue virus after the Zika epidemic in Brazil Anderson Fernandes

Lyinginwait:theresurgenceofdenguevirusaftertheZikaepidemicinBrazilAnderson Fernandes Brito*1, Lais CeschiniMachado*2,Márcio Junio Lima Siconelli*3, Rachel J. Oidtman*4,JosephR.Fauver*1,RodrigoDiasdeOliveiraCarvalho2,FilipeZimmerDezordi2,MylenaRibeiroPereira5,LuizaAntunesdeCastro-Jorge3,ElaineCristinaManiniMinto6,LuziaMárciaRomanholiPassos6,ChaneyC.Kalinich1,MaryE. Petrone1, EmmaAllen1, GuidoCamargoEspaña4,AngkanaT.Huang7,DerekA. T. Cummings7, GuyBaele8,RafaelFreitasOliveiraFranca#5,T.AlexPerkins#4,BeneditoAntônioLopesdaFonseca#3,GabrielLuzWallau#,$,2,NathanD.Grubaugh#,$,11DepartmentofEpidemiologyofMicrobialDiseases,YaleSchoolofPublicHealth,YaleUniversity,NewHaven,CT,USA2DepartmentofEntomology,AggeuMagalhaẽsInstitute,Fiocruz,Recife,PE,Brazil3InternalMedicineDepartment,RibeirãoPretoMedicalSchool,UniversityofSãoPaulo,RibeirãoPreto,SP,Brazil4DepartmentofBiologicalSciencesandEckInstituteforGlobalHealth,UniversityofNotreDame,NotreDame,IN,USA5DepartmentofVirologyandExperimentalTherapy,AggeuMagalhaesInstitute,Fiocruz,Recife,PE,Brazil6MunicipalHealthSecretaryfromRibeirãoPreto,RibeirãoPreto,SP,Brazil7DepartmentofBiologyandEmergingPathogensInstitute,UniversityofFlorida,Gainesville,FL,USA8KULeuvenDepartmentofMicrobiology,ImmunologyandTransplantation,RegaInstitute,LaboratoryofEvolutionaryandComputationalVirology,Leuven,Belgium*Co-firstauthor#Co-seniorauthor$Correspondence:[email protected](G.L.W.);[email protected](N.D.G)

AbstractAfter Zika virus (ZIKV) emerged and caused an epidemic in the Americas in 2016, both Zika and dengueincidencedeclinedinthefollowingyears(2017-2018)toarecordlowinmanycountries.Followingthisperiodof lowincidence,dengueresurgedin2019inBrazil,causing~2.1millioncases.Thereasonsfortherecentfluctuations in dengue incidence and the maintenance of dengue virus (DENV) through periods of lowtransmissionareunknown.Toinvestigatethis,weusedacombinationofepidemiologicalandclimatologicaldatatoestimatedengueforceofinfection(FOI)andmodelmosquito-bornetransmissionsuitabilitysincetheearly2000s inBrazil.OurestimatesofFOIrevealedthat therateofDENVtransmission in2018-2019wasexceptionally low, due to a low proportion of susceptible population rather than changes to ecologicalconditions.ThissupportsthehypothesisthatthesynchronousdeclineofdengueinBrazilmaybeexplainedbyprotectiveimmunityfrompre-exposuretoZIKVand/orDENVinprioryears.Furthermore,wesequenced69genomesofdenguevirusserotype1(DENV-1)andDENV-2circulatinginNortheastandSoutheastBrazil,andperformedphylogeographicanalysestouncoverpatternsofviralspread.WefoundthattheoutbreaksinBrazil in2019were causedbyDENV lineages thatwere circulating locallyprior to theZikaepidemicandspreadcrypticallyduring theperiodof low transmission.Despite theperiodof low transmission,endemicDENVlineagespersistedfor5-10years inBrazilbeforecausingmajoroutbreaks.Ourstudychallengestheparadigm that dengueoutbreaks are causedby recently introducednew lineages, but rather theymaybedrivenbyestablishedlineagescirculatingatlowlevelsuntiltheconditionsareconduciveforoutbreaks.

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IntroductionAfterZikavirus(ZIKV)wasintroducedinBrazilaroundlate20131,2,theresultingepidemicreacheditspeakinMarch2016.ThedeclineofZikacasesinBrazilduring2017and2018wasmirroredbyadeclineinreporteddengue cases. Interestingly, similar patterns were observed throughout the Americas3. The two years ofabnormallylowdengueincidencewerefollowedbyasynchronizedresurgenceofcasesin2019acrosstheAmericas.Thatyeararecordhigh3.1milliondenguecaseswerereportedthroughouttheregion(2.1millionin Brazil alone), with an incidence of 321.58 cases per 100,000 habitants4. These fluctuations in dengueincidence raise several important questions: (1) Did DENV transmission fluctuate or just reportedsymptomaticdenguecases?(2)CanZikaoutbreaksimpactsubsequentdenguevirus(DENV)transmission?(3) Was the 2019 resurgence in dengue caused by new DENV introductions? Considering the globaldistributionofbothZIKVandDENV5,6,answeringthesequestionscanhelpustobetterprepareforandcontrolfutureoutbreaks.

Severalanthropological,epidemiological,andecologicalfactorsmayexplainthedeclineofdengueincidencepost Zika outbreaks. Human interventions, such as enhanced mosquito control, or changes in humanbehaviourinresponsetotheZikaepidemiccouldexplainthedeclineinreporteddenguecases7,8.However,thesechangesdrivenbyhumaninterventionwouldnotbeexpectedtosimultaneouslyoccuracrossadiverseregion.Ecologicalfactors,suchaslocalhumidityandtemperaturemayalsoimpactthetransmissiondynamicsofarboviraldiseases9.AsthemosquitovectorsforDENV,AedesaegyptiandAe.albopictuscantransmitZIKVandchikungunyavirus(CHIKV),changesinclimatewouldalterthetransmissionofallthreeviruses7–9,andcouldbeatleastpartiallyresponsibleforthefluctuationsinDENV.Finally,immunologicalcross-protectionofflavivirusantibodiescanalsoimpactepidemics10,andthepotentialeffectsofapreviousexposuretoZIKVonsecondaryDENVinfectionshavebeendebated.Previousstudiessuggestthatpre-exposuretoZIKVcould(1)leadtoseveredenguediseaseduetoantibody-dependentenhancement11,asobservedinsecondarydengueinfections by distinct dengue serotypes12,13; and/or (2) provide partial protection, leading to less severedisease8,14.With nearly two-thirds of the dengue cases beingmild or asymptomatic6, high levels of cross-protection could lead to less severe infections, and even higher underreporting. This last scenario couldexplainthedeclines indenguecasesobservedincountrieshardhitbyZIKVpriortodengueresurgence in2019,likeinBrazil15,Bolivia16,Suriname17,andNicaragua18.

Theresurgenceofdengueraisesquestionsabouttheoriginofthe2019outbreaks inBrazil.All fourDENVserotypeshavecirculatedthroughouttheAmericassincetheirreintroductionsintothewesternhemisphereinthe1970-80s19–23;however, inmorerecentyears,DENVserotype1(DENV-1)andDENV-2havebecomepredominant inBrazil24.Thus, it isunclear if therecentoutbreakswerecausedbyexistingDENV lineagescrypticallycirculatinginBrazilbeforeandduringtheyearsoflowreporteddenguecases,oriftheyweretheresultsofnewDENVlineagesintroducedfromothercountries.HistoricaldengueoutbreakscausedbyDENV-2inPuertoRico,forexample,havebeencausedbybothreintroductions(cladereplacement)andlocalsurvivalthroughperiodsoflowtransmission25.ThedistinctionisimportantforbothourbasicunderstandingofDENVmaintenanceanddevelopingtargetedcontrolmethods.

To answer these questions,we combined genomic, epidemiological, and ecological data to investigate theresurgence of dengue across Brazil and within two distinct geographic regions. Our estimates of DENVtransmission show that the periods of low incidence in 2017-2018 were caused by low populationsusceptibility rather than environmental conditionsor surveillance gaps.We then sequencedDENV-1 andDENV-2from69clinicalsamplescollectedduring2010,2018,and2019fromNortheastandSoutheastBraziltoidentifytheoriginsandtracethespreadofthevirusesduringtheresurgencein2019.Wefoundthattherecent dengue outbreaks were caused by DENV lineages circulating in Brazil before the Zika epidemic,



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meaningthatthelineagesenduredtheperiodoflowtransmission.Furthermore,thedispersalvelocityofthesepersistentDENVlineagespeakedin2016andslowedwiththedeclineofZikaanddenguein2017.Together,our results indicate that DENV established cryptic transmission for more than five years before causingoutbreaks in 2019, perhaps due to waning cross-protection provided by existing DENV and/or ZIKVpopulationimmunity14,26,ascenariothatmayhaveoccurredacrosstheAmericas.

Results

PatternsofdengueincidenceaftertheZikaepidemicWhiletheannualdengueincidenceinBrazilvariesbyyear,thegeneraltrendinthe21stcenturyhasbeenanincreasingburdenofdisease(Figure1A).In2016,denguecasesexceeded1.6million,whichwasarecordatthetime27.In2017and2018,thenumberofannuallyreporteddenguecasesdeclinedto~250,000,thelowestsince2005 (~200,000;Figure1A). In 2019, dengue cases again rebounded, setting a new recordof~2.1millionreportedcases inBrazil(Figure1A).Weshowthatsimilarpatternsofdengueincidencewerealsoobservedineachofthefivegeographicregionsofthecountry(Figure1B-C).

From2016 to2018,Zika incidence followedasimilarpatternasdengue.AfterZikawas introduced in thecountryinlate20131,2,andspreadundetecteduntilMay201528,thenumberofZikacasespeakedinMarch2016 (Figure1A, Figure S1). Subsequently, dengue casesdroppeddrastically across the country, only toresurgein2019.Onehypothesisforthesuddendecreaseindengueincidenceduring2017and2018isthatZIKVinfectionsprovidedsomecross-protectiveimmunityagainstDENVinfections8,14.Ifaccurate,theriseindengueincidenceduring2019couldrepresentwaningcross-protection.



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Figure1.DengueresurgenceinBrazilfollowinga2-yeardroughtpostZikaepidemic.(A)MonthlydengueandZikacasesinBrazil,from2000to2019.(B)MapofgeographicregionsinBrazil.(C)DenguecasespergeographicregioninBrazil,from2010to2019(y-axisnotinthesamescale).

AnnualdenguevirusforceofinfectionThetrendsindengueincidencecouldbecausedbyDENVtransmissiondynamicsand/orbiasesinsurveillancesystems(Figure1).Commonly,onlysymptomaticinfectionsaredetectedbysurveillance,andtheprobabilityofexperiencingdenguefeverorseveredenguedependsonwhetheranindividualisexperiencingaprimary,secondary, or post-secondary DENV infection29. Changes in the demography and recent history of DENVtransmissioninapopulationcan,throughthismechanism,generatesubstantialinter-annualvariabilityintheprobability that individuals experience dengue fever or severe dengue in a given year30–32. To determinewhethernaturalvariationinthesefactorscouldexplainthedeclineindengueincidencein2017and2018,weestimatedtheforceofinfection(FOI)ofDENVtransmissiononanannualbasisfrom2002through2019.Thismetric,definedastherateatwhichsusceptibleindividualsbecomeinfected,accountsfortheaforementionednaturalchangesintheprobabilityofexperiencingdenguefeverorseveredengueandprovidesamoredirectmeasureofDENVtransmissionthanreportedincidence.

OurestimatesofFOIindicatethattransmissionwasindeedlowin2017and2018(Figure2).WhenwerankedyearsbytheirFOIacrossthe100replicatesthatcomprisedourestimates,wefoundthat2017and2018werenearlyalwaysinthelowerhalfofyearsinallfiveregions,butthelowestonlyintheCenter-Westregionin



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2018(FigureS2).Ourinferredchangesintheprobabilityofdenguefeverorseveredengueconditionaloninfectionwereflatfrom2002through2019(FigureS3),suggestingthatchangesinDENVtransmission,nottheadecline insecondaryandpost-secondary infectionsthatwouldbemore likelytobesevereandtobecapturedby surveillance, likely contributed to thedrop in dengue incidence in 2017 and2018. Thus, ourestimatesofDENVtransmissionmatchthepatternsindengueincidence(Figure1),supportingthescenariothatdenguediddeclinefollowingtheZikaepidemic.

Onecontributingfactortotherelatively lowFOI inthoseyearsmayhavebeenthatsusceptibilitytoDENVinfectionappearedtobeatornearitslowestin2017and2018(FigureS4).Relativetoitsmaximumacross2002-2019,populationsusceptibilityin2017and2018wasaround5%lowerinabsolutetermsand7-10%lowerinrelativeterms.Thisreductioninsusceptibility in2017and2018waslikelyaresultofhighDENVtransmission over several preceding years, which may have provided some within and between DENVserotypeprotection(thoughwedonothavesufficientdataonserotypestoanalyze).Basedonthisanalysis,however,we cannot exclude a possible role for other factors, such as cross-protection conferred by ZIKVinfection14,26,asalsocontributingtoareductionindengueincidenceinthoseyears.

Figure2.DenguevirusforceofinfectionwaslowfollowingtheZikaepidemic.Shadedregionsindicatethe95%credibleintervalsanddarklinesindicatemedianestimate.TheregionsandcolorscorrespondtothemapinFigure1B.

Mosquito-bornevirussurveillanceandtransmissionpotentialIfpastDENVand/orZIKVinfectionsprovidedimmunologicalprotectionagainstDENV,thenthesamepatternsofdenguedeclineshouldfollowthroughouttheAmericasinthewakeoftheZikaepidemic.Weshowthatthedropindengueincidencein2017-2018wasalsoobservedinmanyotherregionsinLatinAmericaandtheCaribbean,demonstratingthispatternwasnotuniquetoBrazil(Figure3A).However,therecouldbeotherfactors contributing to the patterns of dengue incidence that are unrelated to population immunity orsusceptibility, such as: (1) changes inmosquito-borne virus surveillance practices, including surveillance



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“fatigue”(e.g.decreaseinallocatedresources)followinganepidemic;and(2)changingecologicalfactorsthatgovernmosquito-bornetransmission.

Toevaluatethepotentialimpactsofmosquito-bornevirussurveillanceduringandaftertheZikaepidemic,weinvestigated the patterns of reported cases of chikungunya (Figure3B). CHIKV is also transmitted byAe.aegypti and Ae. albopictus, but as an alphavirus, it would not be affected by previous exposure to theflavirususes,ZIKVandDENV.Thus,ifCHIKVfollowedsimilarpatternsasZIKVandDENV,itwouldsuggestthatsystematic changes - ecology and/or surveillance - would have also played a large role. We found thatchikungunyacases,whichalsopeakedinBrazilduring2016,graduallydeclinedthrough2019,anddidnotmatchtherecentpatternsofdengueincidence(Figure3B).AsthedenguepatternsinBrazilmatchthosefoundthroughouttheAmericas(Figure3A),butreportedchikungunyacasesinBrazildonotfollowthesamesteepdeclineandrebound(Figure3B),thismaysuggestthatchangesinsurveillancearenotaprimarycauseoftheobserveddenguepatterns8(Figure1).

Asdengueoutbreakswithinaregioncanbesynchronous,driveninpartbylargeclimaticshifts(e.g.ElNiño)33–36,wesoughttodetermineifrecentecologicalchangescouldhavealteredvirustransmissionpotentialbyAe.aegyptimosquitoes.Forthisanalysis,weusedIndexP,ametricthatusesdynamictemperatureandhumiditydatawithepidemiologicalfactors(Figure3C)37,toestimatethetransmissionpotentialofmosquitoesfrommajorurbanareasintheregionshistoricallymostaffectedbydengue:NortheastandSoutheastBrazil(Figure1B-C).OuranalysisshowsthatIndexPwasnotnotablydifferentbetween2016-2019(Figure3C),anddoesnotaccountforthedifferencesindenguecasesinthoseregions(Figure1C).Thus,basedondengueincidenceintheAmericas,chikungunyaincidenceinBrazil,andIndexP,weconcludethatthechangesindenguepatternswerelikelynotduetochangingsurveillanceeffortsorclimate.

No

Figure3.Lowdenguecasesin2017-2018notprimarilyduetosurveillanceorclimate.(A)Denguecasesfrom2016-2019 reported to the Pan-AmericanHealthOrganization aggregated by region in the Americas. A sharp decrease in



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denguecaseswasobservedin2017-2018indistinctsubcontinentalregionsintheAmericas:Northern(fromVenezuelato FrenchGuyana),Western (fromColombia to Bolivia) and Southern SouthAmerica (fromParaguay to Argentina),Caribbean, Central America, and Mexico. (B) In Brazil, the comparative epidemiological curves of dengue andchikungunyacasesbeforeandaftermajorZikaoutbreaksin2016.(C)IndexP(transmissionpotential)estimatedfromdistincturbanareasinParaíba(PB,northeastBrazil)andSãoPaulo(SP,southeastBrazil)states.

VirusgenomicsrevealsthetimingoftheDENVoutbreaklineagesWhendengueincidenceresurgedthroughoutBrazilin2019(Figure1),itwasunclearifitwascausedbynewDENV introductions or by lineages already established in the country, which survived two years of lowtransmission. To investigate, we sequenced DENV from the recent outbreaks in Northeast Brazil (mainlyaffectedbyDENV-1)andSoutheastBrazil(mainlyaffectedbyDENV-2)24,regionsthattypicallyhavehigherdenguecases than therestof thecountry (Figure1C).Wesequenced43DENV-1genomescollected from2018-2019denguecasesidentifiedintheNortheaststatesofParaíbaandAlagoas.FromtheSoutheaststateof SãoPaulo,we sequenced threeDENV-1genomes from2018, fourDENV-2genomes from2010, and19DENV-2genomesfrom2019(TableS1).TheDENVsamplesfromSãoPauloweresequencedbyplacingserumfromdenguecasesonFTAfilterpapercards(whichtherebyinactivatedthevirus38)andshippingthemtoYaleUniversity(Methods;FigureS5),therebyhighlightinghowthissimplemethod39canbeusedtosupplementvirussequencingwhenlocalcapacitiesarelimited.

Touncovertheoriginsoftherecentdengueoutbreaks,wecombinedour46DENV-1and23DENV-2genomeswithothersthatwereavailable(seeMethods),andinferredtime-resolvedphylogenetictrees(DENV-1=200totalgenomes,Figure4;DENV-2=220totalgenomes,Figure5;root-to-tipestimatesofevolutionaryrate,FigureS6).Ourdatashowthatthetimetomostrecentcommonancestor(tMRCA)DENV-1virusessequencedfromParaíbaandAlagoaswasmid-2012(95%Bayesiancredibleinterval(BCI)2011.79-2013.33;Figure4),andthetMRCAforDENV-2virusessequencedfromSãoPaulowasearly2014(95%BCI2013.33-2014.61;Figure5),whichwas independently confirmed40. As there are farmore availableDENV envelope proteincodingsequences thanwholegenomes41–43,werepeatedouranalysisusing1250DENV-1(FigureS7)and1202 DENV-2 (Figure S8) envelope sequences reported in previous studies41–43, and we found similarclusteringpatternsandancestralphylogeographicorigins.Overall,ourdataandanalysesrevealacommonpattern:lineagesofDENV-1andDENV-2causingoutbreaksinSoutheastandNortheastBrazilweremostlikelyintroducedanddescendedfromvirusescirculatinginthoseregionsbeforetheZikaepidemic.

OriginsandspatialdispersalofDENV-1lineagescirculatingfrom2012-2019OurphylogeneticanalysisrevealedthatDENV-1lineagescausingthe2019outbreakinNortheastBrazilhadbeencirculatingundetectedintheregionsinceatleastmid-2012(Figure4).Usingnear-completegenomesfromDENV-1isolatesfromBrazilandothercountriesintheAmericassincethe1980s,wethenexplored(1)thegeneticrelatednessofDENV-1genomesintheNortheastandSoutheast,(2)howlongtheoutbreaklineageshavebeencirculatinginBrazil,and(3)thepatternsofwithin-regionspreadduringtheperiodofcrypticDENV-1transmission.

DENV-1was first detected in Brazil in 1981 (Figure S7) and, up until the 1990s,was themain serotypecirculatingtherealongwithDENV-244.TheprimaryDENV-1lineagessequencedfromBrazilareclassifiedintofive clades: BR1-BR541,42 (Figure 4A, Figure S7). Our analysis shows that the 2019 DENV-1 outbreak inNortheastBrazil,andatleastonecaseinSoutheastBrazil,wasprimarilycausedbytheBR5lineagevirusesthat have been circulating in Brazil formore than a decade (tMRCA = 2005-2007;Figure 4A). Thus, theintroductionoftheBR5lineageintoNortheastBrazilaroundmid-2012waslikelyfromadomesticsource.Inaddition,oneofoursequencedDENV-1genomesfromAlagoasstate(NortheastBrazil)clusteredwiththeBR4



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clade,andthreeofoursequencedDENV-1genomesfromSãoPaulostate(SoutheastBrazil)clusteredwiththeBR3clade,indicatingthecontinuedco-circulationofmultipleDENV-1lineagesinBrazil(Figure4A,FigureS7).

To reconstruct the regional spreaddynamics ofDENV-1 lineageBR5 since its introduction intoNortheastBrazil,weperformedcontinuousphylogeographicanalysistomapviralspatiotemporalspread(Figure4B).WefoundthatDENV-1circulatedundetectedintheJoãoPessoametropolitanareaforatleastoneyearthrough2014 (region 1, in Figure 4B), before moving to the metropolitan region of Campina Grande, anotherimportanturbanareainParaíba(region2,inFigure4B).Inthisregion,DENV-1establishedlocaltransmissionchains in surrounding municipalities from 2015 to 2016 (Figure 4B), eventually also spreading back toSoutheastBrazil(SãoPaulostate),whereitwasdetectedin2019(Figure4A,inpurple).

To estimate the dispersal velocity of cryptic spread, we used spatiotemporal information extracted fromthousandsofposteriortreesinferredtoinvestigateDENV-1localspread(Figure4C-D).Wefoundthatlikelyin early 2016, when Zika cases were peaking in the Northeast (Figure 1C, Figure S1), DENV-1 starteddispersingtowardsthewesternmostpartofParaíbastate(region2to3,Figure4B-C)andreacheditshighestdispersionrate(69.1Km/yearinmid-2016;Figure4D).Itwasfollowedbyalargedropindispersalvelocity,whenmainlylocal,shortrangetransmissionswerepredominantintheregionafterlate2017(Figure4D).Thus,ouranalysissuggeststhatthespreadofDENV-1intheregiondeclinedalongsidetheZikacasesin2017,andtheoutbreakin2019waslikelycausedbylocallyestablishedviruses.



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Figure4.RegionalemergenceandcryptictransmissionofDENV-1causingrecentoutbreaksinNortheastBrazil.(A) Time-resolved phylogeny of DENV-1 circulating in the Americas since 1986 (n=200). Branch colors representreconstructedancestrallocationsusingdiscretephylogeography.DENV-1genomessequencedinthisstudy(n=46)arehighlightedwithasterisks(*).(B)ContinuousphylogeographyshowingthelocalspreadofDENV-1intheNortheastBrazilstates of Paraíba (PB), Alagoas (AL), and likely Pernambuco (PE). Areas numbered as 1 (João Pessoa), 2 (CampinaGrande), and 3 (Coremas) correspond to the main location where DENV-1 circulated. Shaded areas representuncertainties,expressedasthe80%highestposteriordensity(HPD)ofthepossiblelocationsoforiginofviralancestors.(C)ThemainDENV-1outbreakcladeplottedasmovementvectorsin(B).Theviolinplotshowstheposteriordensityinterval for the tMRCA.Numbers refer to areas shown in (B). (D)Weighted lineage dispersal velocity through time,reachingitspeakaroundJune2016,withmeanvelocityof69.1km/year(confidenceinterval,45.07-90.91Km/year).



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TobetterdepictthedynamicsofspreadinNortheastBrazil,thesinglevectorleadingtoSãoPaulowasnotconsideredinthecalculationsofdispersalvelocity.

OriginsandspatialdispersalofDENV-2lineagescirculatingfrom2013-2019Similar to DENV-1 during the outbreak in Northeast Brazil (Figure 4), we found that the 2019 dengueoutbreakintheSoutheaststateofSãoPaulowascausedbyaDENV-2lineageestablishedintheregionsinceat least2014(Figure5).ToinvestigatethespatialdynamicsofDENV-2inSoutheastBrazil,weperformedsimilarphylogeographicanalysesasdescribedforDENV-1.

Combining our 23 DENV-2 genomes primarily from Ribeirão Preto (region 1 in Figure 5B) with the 20genomesrecentlysequencedbydeJesusetal.40fromAraraquara(region2)andSãoJosédoRioPreto(region3)municipalitiesinSãoPaulostate,wefoundthe2019outbreakwasprimarilycausedbyadifferentDENV-2lineage(BR4)thanwhatwasdetectedduringthe2010outbreakinthesameregion(BR3;Figure5A;FigureS8).However, there is evidence that theDENV-2BR3clade,whichemerged inBrazil around2004, is stillcirculatinginSoutheastBrazil(Figure5A)40.TheclosestsequencedDENV-2ancestorstothenewBR4lineagearefromtheCaribbean,whichwasintroducedintoBrazilnolaterthan2014(95%BCI,2013.33-2014.61,Figure5C).

WereconstructedtheregionaldispersalhistoryofDENV-2lineageBR4touncoverhowthevirusspreadinSoutheastBrazil duringmostly cryptic transmission (Figure5B-D). Following the sameapproachused toinvestigateDENV-1diffusionthroughtime,wefoundthatDENV-2wasmostlikelyintroducedinSãoPaulothroughthemunicipalityofRibeirãoPreto(region1)around2014,where itcirculatedundetected for1-2years(Figure5B-C).From2015-2017theviruslineagereacheditsperiodoffastestdispersal(66.2km/year)asitspreadtowardsAraraquaraandSãoJosédoRioPreto(regions2-3;Figure5C-D).Onceestablishedinthesenewareas,DENV-2circulatedlocallyviashortrange,sustainedtransmissionchains,asrevealedbyitslowdispersalvelocitythrough2018-2019(Figure5D).SimilartoDENV-1lineageBR5inNortheastBrazil,thepatternsofDENV-2lineageBR4dispersalinSoutheastBrazilfollowedthefallofZikacasesinBrazil(Figure1),with2019dengueoutbreaksbeingcausedbylocallyestablishedvirusesratherthannewintroductions.



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Figure 5. Regional emergence and cryptic transmission of dengue 2 viruses causing recent outbreaks inSoutheastBrazil.(A)Time-resolvedphylogenyofDENV-2circulatingintheAmericassince1987(n=220).Branchcolorsrepresentreconstructedancestral locationsusingdiscretephylogeography.DENV-2genomessequencedinthisstudy(n=23) are highlighted with asterisks (*). (B) Continuous phylogeography showing the local spread of DENV-2 inSoutheastBrazil,stateofSãoPaulo(SP).Areasnumberedas1(RibeirãoPreto),2(Araraquara),and3(SãoJosédoRioPreto)correspondtothemainlocationwhereDENV-2circulated.Shadedareasrepresentuncertainties,expressedasthe80%highestposteriordensity(HPD)of thepossible locationsoforiginofviralancestors.(C)MainDENV-2outbreakclade in (A),plottedasmovementvectors in (B).Theviolinplotshows theposteriordensity interval for the tMRCA.Numbersrefertoareasshownin(B).(D)Weightedlineagedispersalvelocitythroughtime,reachingitspeakaroundJanuary2016,withmeanvelocityof66.2km/year(confidenceinterval,31.3-103.5km/year).



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DiscussionResurgenceofdenguefollowingaperiodoflowtransmissionFollowingthemajorZikaepidemicin2016,dengueincidenceremainedlowthroughouttheAmericasfortwoyears(2017-2018),resurginginBrazilandelsewherein2019(Figure1).Thereasonsforthedrasticdeclinesindenguecaseshavebeendebated7,8,butevidencetoexplainsuchphenomenaarescarce.Inthisstudywecombinedgenomic,ecologicalandepidemiologicaldata toexplain thedynamicsofdengueresurgence.WefoundthatDENVtransmissionlikelydecreasedin2017-2018duetolowpopulationsusceptibility(Figure2),ratherthanenvironmentalconditionsorsurveillancegaps(Figure3).Usingviralgenomescollectedin2010,2018,and2019,weuncoveredtheoriginsofrecentdengueoutbreaksinBrazil,whichwerecausedbyendemicDENVlineagescirculating inBrazil for5-10years(Figures4and5).This findingrevealedthatDENVcanendureperiodsoflowtransmission,andresurgewhenconditionsaresuitable.OurresultssuggestthatDENVcrypticallycirculatedin2017-2018beforeresurgingayearlater,likelyasaresultofwaningcross-protectionconferredbypriorDENVand/orZIKVpopulationimmunitythatmayhaveplayedoutinmanycountriesacrosstheAmericas.

Lowpopulationsusceptibilitycontributedtolowdengueincidencein2017-2018Our annual estimates of DENV FOI in the five regions of Brazil suggest that the number of susceptibleindividualsfrom2017-2018droppedtosomeofthelowestlevelssince2002(Figure2).Wefoundsimilardropsinsusceptibleindividualsduringotherperiodsoflowreporteddengueincidence,suchas2004-2005.Amajorcaveatofthisanalysis,however,isthatweestimatedFOIusingalldenguecasecounts,regardlessofserotype.ThusouranalysisdoesnotcapturetheindividualtransmissiondynamicsofthefourDENVserotypes,whichareknowntoco-circulateinBrazilatleastsince201045.Still,transmissionofallDENVserotypeswaslowduring2017-2018,assuggestedbythelowreportedoverallincidence.

Whilethedecreaseindengueincidencein2017-2018mayhaveresultedfrompopulationimmunitybuildingduringyearsofhighincidence(Figure1),exposuretootherflavivirusescouldhavealsoplayedarole14.Recentstudies demonstrated that immunity from previous ZIKV infections can neutralize subsequent DENVinfections by all serotypes26, without exacerbating the severity of secondary heterologous infections byDENV46. This phenomenon could have led to higher numbers of asymptomatic or mild dengue cases47,resulting in low reporting of cases not only in Brazil, but also in most countries in the Americas, whichexperienced similar patterns of presumed low dengue cases after Zika outbreaks. Although the cross-protectionofZIKV-inducedimmunityonDENVinfectionsmaylikelywane,itsmodulatoryeffectsonDENVpathogenesis could not only explain the decline of dengue in 2017-2018, but also its resurgence in thefollowingyears,allovertheAmericas48.

LimitedcontributionofclimateandmosquitocontrolondenguepatternsAnimportantfindingofourstudywasthatenvironmentalconditionswerelikelynottheprimarycauseofthefluctuationsindengueincidenceinBrazil.DENVtransmissionishighlydependentonclimatefactors,suchashumidity and temperature37. By using climate-dependent and climate-independent data, we estimatedmosquitosuitabilityinfourmajorurbanareasinthestatesofParaíba(Northeast)andSãoPaulo(Southeastregion;Figure3C)andfoundthatconditionsremainedsuitableformosquito-bornevirustransmission.Thus,wefinditunlikelythatclimatichadanotableeffectontheobserveddenguechangesduringthisstudyperiod.

On the other hand, human intervention onmosquito populations following the Zika epidemic could haveimpactedDENVtransmission8.AfterWHOdeclaredZikaaPublicHealthEmergencyofInternationalConcern(PHEIC) in February 2016, Brazil’s Ministry of Health allocated extra funds to implement measures ofmosquito control, which included campaigns to raise awareness and provide information about self-



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protectionagainstmosquito-borneviralinfections49,andtoeliminatemosquitobreedingsitesinvulnerablecommunities50. In this way, Brazil’s preparedness after the Zika epidemic in 2016 may account for lowtransmissionofmosquito-borneviruses,includingDENV,inthefollowingyears.ThiscouldextendtootherpossibleoutcomesoftheZikaepidemic,suchaschangestosurveillanceprograms(e.g.decreaseinfundingandresources)orchangesinhumanbehaviour(e.g.avoidanceofmosquitoes).Unfortunately,dataaboutthemosquito control programs, surveillance strategies, and human behavior from our study areas were notavailableandcouldnotbeincorporatedinouranalyses.However,giventhesynchronyofdenguethroughouttheAmericasduring2016-2020(Figure3A),thechangesinincidencearemorelikelyduetobiologicalfactorsthancoordinatedhumanactivities.

EndemicdengueviruseslineagesresponsibleforrecentoutbreaksDespitethelowdengueincidencein2017-2018,wefoundthatDENVlineagesalreadycirculatinginBrazilfor5-10yearsre-emergedtocauseoutbreaksintheSoutheastandNortheastregionsin2019.Thisdemonstratesthat(1)majordengueoutbreaksmaynotbecausedbyrecentvirusintroductionsand(2)DENVcansurviveperiodsofhighpopulationimmunitythroughlow-levelcryptictransmission.The2019outbreakscausedbyDENV-1inNortheastandSoutheastBrazilincludedatleastthreeendemiclineages,namedsequentiallybasedontheirdateofintroductioninBrazil41,42:BR3,BR4,andmainlyBR5(Figure4).The2019outbreakscausedbyDENV-2inSoutheastBrazil(SãoPaulostate)includedthelineagesBR3andmainlyBR4(Figure5),asalsoreportedinarecentstudy40.OurcontinuousphylogeographicanalysesforDENV-1andDENV-2indicatethatfollowingintroduction,lineagesgothroughperiodsofregionaldispersalbeforebecomingestablishedinanurbanarealeadingtoalocaloutbreak.

Although our DENV genome sampling in Northeast Brazil was spatially heterogeneous, our sampling inSoutheast Brazil was highly focused on two major urban areas. This may have introduced biases in ourpatternsofDENVspreaddepictedinourcontinuousphylogeneticanalyses.FuturestudiesinvestigatingthegenomicepidemiologyofDENV,oranypathogen,shouldideallyconsidertheinclusionofgenomessampledintimesandlocationsinsuchawaytomatchtheincidenceofdiseasetoensureabetterreconstructionofthegeographicpatternsofspread.

FuturedirectionsandimplicationsOurstudychallengestheparadigmthatdengueoutbreaksarecausedbyrecentlyintroducednewlineages,butrathertheymaybedrivenbyestablishedlineagescirculatingatlowlevelsuntiltheconditionsareconducivefor outbreaks. How DENV lineages can persist undetected through long periods of low transmission isuncertain,andshouldbefurtherinvestigated.Furthermore,theoutcomesofthepresentstudydonotdirectlyidentifywhatcausedthefallandriseofdengue,observedinseveralcountries15,16,17,18,butourdatasupportahypothesispertainingtotheroleofthe2016Zikaepidemicandpriordengueoutbreaksinthisphenomenon.FurtherresearchandcohortstudiesarerequiredtoinvestigatewhetherpreviousexposuretoZIKVprovidestransientprotectionagainstDENVinfectionorseverediseaseoutcomes,andif ithasasimilareffectonallDENVserotypes.AsZIKVandDENValsoco-circulateinotherpartsoftheworld,understandingtheseimmuneinteractions may help us to better forecast outbreaks. Furthermore, data about governmental mosquitocontrolprogramsandpublichealthcampaignsshouldbemadeopenlyavailabletobetterevaluatetheefficacyoftheseactivitiesoncontrollingoutbreaks.Finally,weadviseforsustainedgenomicsurveillanceofDENVtodetectcrypticlineagesinanefforttoplanfordengueresurgence.Collectively,ourstudyrevealednewinsightsinto endemic DENV transmission and spread, which provides a basis for developing targeted controlstrategies.



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Methods

EthicsHuman sampling fromParaiba andAlagoa states used in this studywas approved for the Research EthicCommittee(REC)fromtheAggeuMagalhaesInstitute(IAM)undertheCAAEnumber10117119.6.0000.5190.HumansamplingfromSãoPaulostateusedinthisstudywasapprovedbyRECfromHospitaldasClínicasdeRibeirão Preto (HCRP) process number 12603/2006 and also by DAEP/CSE-FMRP-USP project number19/2007.Denguevirussequencingandanalysisofade-identifiedandlimiteddatasetattheYaleSchoolofPublicHealthwasdeterminedtobeexemptfromhumanresearchdeterminedbyalimitedYaleInstitutionalReviewBoard(IRB)review(IRBprotocolID:2000025320).

EpidemiologicaldataDengue,ZikaandchikungunyacasedataperepidemiologicalweekinBrazilwereobtainedfromtheMinistryofHealthofBrazil,fromitsSINANdatabase51anditsepidemiologicalbulletins52,andsharedbytheInfectiousDiseaseDynamicsGroupatUniversityofFlorida(UF-IDD).DenguecasedataperyearinothercountriesintheAmericaswereobtainedfromPAHO4.LinkstoalldatasetscanbefoundinDataAvailability.

EstimatingforceofinfectionWeestimatedtheforceofinfection,λy,r,ofDENVonanannualbasisforeachyear,y,between2002and2019foreachregion,r.Theseestimateswereinformedbythenumberofcasesofdenguefever,Fy,r,a,andseveredengue,Sy,r,a,foreachyear,region,andage,a.Wecalculatedthelikelihoodofagivenseriesofannualforcesofinfectioninregionr,𝜆" ,as

𝐿(𝜆") = ( )*[,-,/,0|2/,34,/]4-,/,0*[6-,/,0|2/,37,/]7-,/,08

9(:[4-,/,0|;/,<4,/]=:[7-,/,0|;/,<7,/])

,-,/,0!6-,/,0!,(1)

whereϱF,randϱS,rareregion-specificprobabilitiesofreportingacaseofdenguefeverorseveredengue,respectively,and𝐸[𝐹(,",)|𝜆", 𝜌,,"]and𝐸[𝑆(,",)|𝜆", 𝜌6,"]aretheexpectednumbersofcasesofdenguefeverandseveredenguepredictedbythemodel.Thisassumesthatobservedcasesofeachtypeineachyear,region,andageareindependentPoissonrandomvariables.

Wecalculatedtheexpectednumberofcasesofdenguefeveras𝐸[𝐹(,",)|𝜆", 𝜌,,"] = 𝜎(,",)D 1 − 𝑒HI2-,/ 𝛾,D + 𝜎(,",)L 1 − 𝑒HM2-,/ 𝛾,L + 𝜎(,",)NO 1 − 𝑒H2-,/ 𝛾,NO 𝜌,,"𝑁(,",) ,(2)

where𝜎(,",) = {𝜎(,",)D , 𝜎(,",)L , 𝜎(,",)NO }areprobabilitiesofhavingexperienced0,1,or2+previousDENVinfections,𝛾, = {𝛾,D, 𝛾,L, 𝛾,NO}areprobabilitiesofexperiencingdenguefeverconditionaloninfectiongiven0,1,or2+previousDENVinfections,andNy,r,aisthepopulationofindividualsofageainregionrinyeary.Thecalculationfor𝐸[𝑆(,",)|𝜆", 𝜌6,"]issimilar.

ProbabilitiesofhavingexperiencedagivennumberofpreviousDENVinfectionsdependontheannualforceofinfectionexperiencedineachyearofaperson’slife.Inthefirsttwoyearsoflife,𝜎(,",D ={1,0,0}and𝜎(,",L = {𝑒HI2-9T,/, 1 − 𝑒HI2-9T,/, 0},becauseweassumethat,atmost,oneDENVinfectionispossibleineachyearoflife.Forallotherages,

𝜎(,",)D = )

UVL 𝑒HI2-9W,/ (3a)

𝜎(,",)L = )XVL ( U:UZX 𝑒HI2-9W,/) 1 − 𝑒HI2-9[,/ ( U:U\X 𝑒HM2-9W,/) (3b)

𝜎(,",)NO = 1 − 𝜎(,",)D − 𝜎(,",)L , (3c)



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where𝜁isanindexforayearinwhichanindividualwasnotinfectedand𝜉isanindexforayearinwhichanindividualwasinfected.For2001andearlier,wetreatedforceofinfectionasthemeanof𝜆" .Toavoidkeepingtrackofallpossiblepairsofyearsinwhichanindividualcouldhaveexperiencedtwoinfections,wecombinedtheproportionofindividualswhohadexperiencedtwoormoreinfectionsineqn.3c.Giventhatmostinfectionsresultingindenguefeverorseveredenguelikelyresultfromprimaryorsecondaryinfections53,weviewedthisapproximationasacceptable.Alsointheinterestofmodeltractability,weassumedthatserotypeswereevenlydistributedwithinandacrossyearsandthattheywereidenticalintermsofinfectiousness,virulence,andothertraits,ashavepreviousanalysesofage-stratifiedcasedata54.

Weusedmaximum-likelihoodinferencetoestimate𝜆" separatelyforeachregionrconditionalon𝛾, ,𝛾6,ϱF,r,andϱS,r.Toaccountforuncertaintyinthelatterparametersthatwedidnotestimate,wetook100independent,randomdrawsofthemfromuniformdistributionsspecifiedinTableS2for𝛾, and𝛾6.BecauseestimatesofϱF,randϱS,rwerenotreadilyavailableintheliterature,wedefinedplausiblevaluesofϱF,r,andϱS,rasthosecompatiblewith𝜌D = 𝛾,D𝜌, + 𝛾6D𝜌6,where𝜌Disdefinedastheprobabilityofreportingacaseresultingfromaprimaryinfectionandwaspreviouslyestimatedtorange0.1-0.9inBrazil54.Givendrawsof𝛾, and𝛾6fromuniformrangesdefinedinTableS2anddrawsofϱF,randϱS,rcompatiblewith0.1<𝜌D<0.9,wethenobtainedmaximum-likelihoodestimatesof𝜆" .Weinitializedtheoptimizationalgorithmatvaluesof

𝜆(," = − 𝑙𝑛 1 − 𝑚𝑖𝑛{0.5, 𝐸[𝛾,]HL𝑚𝑎𝑥{1, ) 𝐹(,",)}/ ) 𝑁(,",�} ,(4)

whichcorrespondtosimplifiedestimatesbasedonlyondenguefevercasesandignoringimmunityfromyearsprecedingy.

MosquitotransmissionpotentialestimatesWeusedtheBayesianapproachdevelopedbyObolskietal.37toestimatetheweeklytransmissionpotential(IndexP).Briefly,weobtaineddailytemperatureandrelativehumidityrecordsforfourcitiesinBrazilfromopenweathermap.org.Wecombinedthesedatawithecologicalandentomologicalpriorsdocumentedintheliterature(TableS3)usingtheRpackageMVSE37toestimatedailytransmissionpotential,whichwethenaggregatedbyweek.

ClinicalsamplecollectionandvirusdiagnosticsOverview:SerumsamplesfromdenguecaseswerecollectedfromtworegionsinBrazil:SãoPaulostateintheSoutheast,and;ParaíbaandAlagoasstatesintheNortheast.SamplecollectionlocationanddatesareprovidedinTableS1.Allpatientspresentedatleastwithfeverandtwoormoresymptomssuchasnausea,vomiting,rash,myalgia,headache,retroorbitalpain,petechiaeorpositivesnaretestandleukopenia.

SãoPaulostate:DenguepatientserumsampleswerecollectedatHospitaldasClínicasfromRibeirãoPretoMedical School and at Basic Health Units (UBDS) distributed throughout the municipality. Dengue virusinfectionwasfirsttestedbyarapidIgM/IgGtest(DengueDUOECOtest,ECODiagnóstica,Corinto,MG,Brazil)orNS1ELISA(FOCUSDiagnostics,Cypress,CA,USA).PositiveIgM/IgGorNS1testswerethenconfirmedbyRT-qPCRusingthefollowingprotocol.RNAfromtheserumsampleswereextractedusingKASVI(MobiusLifeScience,Pinhais,PR,Brazil)accordingtothemanufacturer'srecommendations.RT-qPCRwasperformedinone-step using TaqMan Fast Virus 1-StepMasterMix (Applied Biosystems), following themanufacturer'srecommendations. Primers and probes used were: FD1: 5'-GCACCAGGTGGGAAACGA-3'; RD1: 5'-TAGGAGCTTGAGGTGTTATGG-3', DENV-1 probe: FAM-CTACAGAACATGGAACAAT-MGB and FD2: 5'-



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CTAAATGAAGAGCAGGACAAAAGGT-3'; RD2: 5'-ATCCATTTCCCCATCCTCTGT-3', DENV-2 probe: FAM-TGCAAACACTCCATGGTA-MGB.Thereactionwasperformedinthe7500FastReal-TimePCRSystem(AppliedBiosystems).

Paraíba and Alagoas states: Dengue patient serum samples were collected by the Public Health CentralLaboratory(LACEN)ofeachstateandsenttotheArbovirosesReferenceLaboratoryattheAggeuMagalhãesInstitute-Fiocruz inRecife,Pernambuco, forviral identification.Denguevirus infectionsweredetectedbyusingtheQIAampViralRNAkit(Qiagen,Hilden-Germany)toextractRNAfromtheserumsamplesfollowedbyusingaDENV-1-4Real-TimeRT-PCRAssayfollowingtheCDC'srecommendations55.

VirusgenomesequencingOverview:Duetolimitednext-generationsequencing(NGS)capacityavailabletotheresearchersinSãoPaulostateatthetimeofconductingthisstudy,dengueclinicalsamplesfromthisstatewerepreservedonFTAfilterpaper cards and shipped toYaleUniversity formetagenomic virus sequencingusing an IlluminaNovaSeqplatform, as described below. Fromdengue virus samples collected in Paraíba andAlagoas states, a localIlluminaMiSeqavailableattheAggeuMagalhaesInstitutewasusedforamplicon-basedvirussequencing.

MetagenomicvirussequencingfromsamplesstoredonFTAcardsSãoPaulostate:FrozenserumfromDENV-1andDENV-2positivepatientswerethawedand50uLwasmixedwith10-15μLofRNAlater(Ambion,USA).Around55–65μLofthemixturewasspottedontoFTACards(WhatmanTM,GEHealthcareBio-SciencesCorp,Piscataway,NJ,USA)anddriedatroomtemperature.Eachcard(8,5 x 7,5 cm) was loaded with 16 different samples, respecting a minimal distance among the samplesavoidingthesamplecross-contamination.ThecardswerestoredatroomtemperatureuntilshipmenttoYaleUniversity.

Uponreceiving,FTAcardscontainingserumwerefrozenat-80untilprocessing.AscalpelwasusedtocutoutanddiceentireserumspotsfromFTAcards.Thescalpelwassterilizedbetweensamplesbysubmerginginto70%EtOHfollowedbysubmerginginto10%(v/v)bleach3times.ToeluteserumfromFTAcards,dicedpiecesfromeachsamplewereplacedin350μLof1xTE,androckedat4°Cfor16hours.RNAwasextractedfrom200μLof1xTEelutionusingtheMag-BindViralDNA/RNAkit(OmegaBio-tek,USA)andelutedinto25μLofwater.DENV-2sampleswerethenscreenedviaanRT-qPCRassayusingFD2/RD2primerswiththeiScript™One-StepRT-PCRKitWithSYBRGreen(Bio-Rad,USA).DENV-2samplesthatproducedacyclethresholdvalue>33andauniquemeltingcurvewereprocessedforNGS,andallDENV-1wereprocessed.

DENV-1andDENV-2RNAeluted fromFTAcards fromSãoPaulostateweresequencedusinganunbiasedmetagenomicsapproachon the IlluminaNovaSeqat theYaleCenter forGenomeAnalysis.To increase theoverallquantityofinput,weproceededwithaprimer-extensionpre-amplificationSISPAapproachtogeneraterandomly amplified cDNA as described previously 56,57. Briefly, RNA was incubated with 1 μL Primer A(40pmol/μL)and0.5ulofa10mMdNTPmixfromtheSuperScriptIVFirst-StrandSynthesisSystem(ThermoFisherScientific,USA)at65°Cfor5minutes.First-strandcDNAsynthesiswascarriedoutwiththismixtureusingtheSuperScriptIVFirst-StrandSynthesisSystemwithouttheadditionofrandomhexamersaccordingtomanufacturer'sprotocol. Second-strandsynthesiswasperformedusing theSequenaseVersion2.0DNAPolymerase System (Thermo Fisher Scientific, USA) as previously described 56. Second-strand synthesisreactionswerecleanedusing0.8:1ratioofMag-BindTotalPureNGS(OmegaBio-Tek,USA)beadstovolumeofsample.Followingtwowashesofbeadswith70%EtOH,cDNAwaselutedintonucleasewater.cDNAwasincubatedwith2.5μLofPrimerB(40pm/μL)andamplifiedusingQ5HSHigh-Fidelity2xMM(NewEnglandBiolabs,USA)for15cyclesaccordingtomanufacturer'sinstruction.PCRproductwaspurifiedusinga0.8:1



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ratioofMag-BindTotalPureNGSbeadstovolumeofPCRmix.PCRproductsforeachsamplewerequantifiedusingtheQubit1XdsDNAHSAssayKit(ThermoFisher,USA).

Atotalof5ngofdsDNAwasusedas input for librarypreparationusingtheKAPAHyperPrepKit(Roche,Switzerland) with NEXTflex™ Dual-Indexed DNA Barcodes. Following ligation of adaptors and barcodes,individualsampleswereamplifiedusinguniversalIlluminaprimersandKAPAHiFiDNAPolymerase(Roche,Switzerland)according tomanufacturer's instructions.Librarieswerepurifiedusing1:1ratioofMag-BindTotalPureNGSbeadstovolumeoflibrary,quantifiedusingtheQubit1XdsDNAHSAssayKit,andpooledbyequalconcentrations.Thefinalpooloflibrarieswassizeselectedto500-600b.p.usingthePippinPrep(SageScience,USA),andsizedistributionswereconfirmedusingtheAgilentBioanalyzerHighSensitivityDNAKit(AgilentTechnologies,USA).LibrariesweresequencedusingaportionofalineonaNovaSeqattheYaleCenterforGenomeAnalysis.

ElutionandRNAextractionwereattemptedfromatotalof96serumsamplesstoredonFTAcards.Ofthese,atotal of 60 samplesmet the criteria forNGS (DENV1N=7,DENV2N=53). A total of 56million read pairs(2x150)weregeneratedfrom65libraries, including5controllibrariesthatwereintroducedatthesampleelutionstageandlibrarypreparationstage(TableS1).TheproportionofreadsaligningtoeachrespectiveDENVreferencegenomerangedfrom0-29.9%,althoughthemajorityofsamples(N=52)hadlessthan1%ofreadspassingQCalignedtotheDENVreferencegenome.Eachofthe5controllibrarieshadlessthan15totalreadsaligningtoeithertheDENV1orDENV2referencegenome.Ofthe60samplessequenced,atotalof25(DENV1N=4,DENV2N=21)genomesmeetourthresholdof70%atgreaterthan10Xcoveragetobeincludedinouranalysis(FigureS5).

Amplicon-basedvirussequencingParaíbaandAlagoasstates:TotalRNAfromNortheastBrazilsamplesweresequencedusingawhole-genometiledPCRamplicon-basedapproach58,59.Inbrief,cDNAwassynthesizedusingrandomhexamers(Invitrogen)andProtoScriptIIReverseTranscriptase(NewEnglandBiolabs).Then,theresultingcDNAwassubmittedtoa multiplex PCR using primers covering the entire DENV-1 genomes designed using PrimalScheme(https://primalscheme.com/) 58.DENV-1primer sequences canbe found inTableS4. PCRreactionswereperformedusingfourseparatepoolstominimizeprimercompetition,usingQ5HotStartHigh-FidelityDNAPolymerase(NewEnglandBiolabs).Theresulting~400bpampliconswerequantifiedusingQubitdsDNAHSAssay Kit (Thermo Fisher Scientific Inc.), the four separate PCR reactions were pooled, and 2 ng wereprocessedthroughtheNexteraXTLibraryPrepKit(Illumina,SanDiego,CA,USA)andsequencedontheMiSeqIlluminaplatformfromtheAggeuMagalhaesInstitute-FiocruzemployingaMiSeqreagentkitV3of150cycleswithapaired-endstrategy.

SequencingdataprocessingThegoalofourbioinformaticspipelinewastogeneratecompleteornearlycompleteDENVgenomesequencesforphylogeneticanalysisusingareference-basedconsensusgeneration.Analysiswasconductedonthehigh-performance computing clustershostedby theYaleCenter forResearchComputing. Sequencingadaptors,primersequences(foramplicon-basedsequencing),andlowqualityreadsweretrimmedusingTrimmomatic(version 0.39) 60. Following quality control, paired reads were aligned to a reference DENV1 (Accessionnumber:JX669465.1)andDENV2(Accessionnumber:KP188569.1)genomeusingbwa(version0.7.17)61.Thealigned reads were filtered and output as a .bam file using SAMtools (version 1.9) 62. Sorted .bam filescontainingonlymapped,pairedreadswerevisualizedinGeneiousPrime(version 2019.0.3)63.Consensussequences were generated in Geneious Prime and vcf-annotate (parameters --filterQual=20/MinDP=100/SnpGap=20)andvcf-consensus,whereaminimumof10readswererequiredtocalla



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baseatanygivenpositioninthegenomeandthethresholdtoinsertambiguousnucleotidesintotheconsensussequencewas75%.Regionsofthegenomesthatdidnotreachthe10Xdepthofcoveragecut-offhadan“N”insertedintotheconsensussequence.Finalsequencesthathadgreaterthan70%ofthegenomewithgreaterthan10Xdepthofcoverageallshowedtofittheexpectedmolecularclockforvirusesoftheirserotypes(FigureS5),andwereusedforphylogeneticanalyses.

VirusgenomicdataselectionandalignmentTobuildour initialdatasets,wedownloaded fromGenbankall completegenomesof genotypesofdengueviruses(serotype1and2)commonlycirculatingintheAmericas:DENV-1genotypeV(n=458),andDENV-2genotypeAA(n=814)completegenomes.Genomeswithoutcollectiondatesandlocationinformationwereexcluded.ThesequenceswerealignedusingMAFFT64,manuallycuratedandhadtheiruntranslatedregions(UTR) trimmed. Preliminarymaximum-likelihood (ML) analyseswere performedusing IQTree v.1.6.12 65,withautomaticmodelselectionbythesoftware.UsingTempEst66,weinspectedthesegenomestoidentifymajormolecularclockoutliers,whichwereremoved fromalldownstreamanalyses.Thisyieldedtwohighqualitydatasetswithgenomesevenlysampledthroughtime,allowingoptimalclocksignal(FigureS6):DENV-1(n=458genomes),andDENV-2(n=700genomes).Basedonthesesamples,smallerdatasetswereobtainedbysubsamplingoverrepresentedclades,keepingonlytworepresentativesperdeme,andaddingournewlysequencedgenomes.

DiscretephylogeographicanalysesToinfertheevolutionaryhistoryofDENV-1and2,andunderstandtherecentmajoroutbreaksofdengueinBrazil,weperformedBayesianphylogeneticinferenceusingBEASTv.1.10.467.FortheseanalyseswespecifiedaBayesianskygridcoalescenttreepriorwith50gridpoints68,aGTR+Γ4modelofnucleotidesubstitution,and a strictmolecular clock. Geographic data of sample originswere arranged in a geographic scheme ofsubnational(thefiveregionsinBrazil)andsubcontinentalareas,suchasNorthern(fromVenezuelatoFrenchGuyana), Western (from Colombia to Bolivia) and Southern South America (from Paraguay toChile/Argentina),Caribbean,CentralAmericaandMexico.TheancestraloriginsofvirusescirculatingintheAmericas were inferred using a reversible discrete phylogeography model 69. Using the BEAGLE library(v3.1.0)toacceleratecomputation70,MarkovchainMonteCarlo(MCMC)samplingwasperformedfor100million iterations, and convergence of parameters (ESS > 200) was assessed using Tracer v1.7 71. Afterremoving 10% burn-in, maximum clade credibility (MCC) trees were summarized using TreeAnnotatorv1.10.4,visualizedusingFigTreev1.4.472,andplottedusingbaltic73.

ContinuousphylogeographicanalysesToinferthedispersalhistoryofdengueviruslineagescirculatinginNortheastandSoutheastBrazilinrecentyears,weuseda continuousphylogeographicmethod74 implemented inBEASTv.1.10.4 67.TheseanalysesfocusedontwomonophyleticoutbreakcladesofDENV-1and2genomessequencedinthisstudy(Figure4CandFigure5C).Weusedthesameevolutionarymodelasdescribedabove,usingtheinferredheights(95%HPD)fromsuchanalyses(Figures4Aand5A)asnormalpriordistributionstosetthetMRCAoftheoutbreakclades.Takingadvantageofgeographiccoordinatesassociatedwiththeoutbreakviruses,aCauchyrelaxedrandomwalk(RRW)diffusionmodelwasemployedtoinfercoordinatesassociatedwithancestorsofvirusescausingtherecentoutbreaks(internalnodes).MarkovchainMonteCarlo(MCMC)samplingwasperformedfor150millioniterations,usingtheBEAGLElibrary(v3.1.0)toacceleratecomputation70,andconvergencewasinspectedusingTracerv1.771.Asaresult,weobtained10,000treeswithancestralcoordinatesannotatedateachnode.Afterdiscarding10%of thesampledtreesasburn-in, thedatarecorded in1,000treeswereextractedandplottedingeographicspaceusingthe“seraphim”Rpackage75.



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Data,code,andanalysisavailabilityThegenomesgeneratedinthisstudyareavailableonNCBI(accessionnumbers:willbeprovidedinthefinalsubmission;genomicdatacanbefoundinourgithubrepository),anddatasetsusedinouranalysiscanbefoundathttps://github.com/grubaughlab/DENV-genomics/tree/master/paper1.

AuthorcontributionDesignedthestudy:AFB,TAP,RFOF,GLW,andNDG.Performedthesequencing:LCM,MJLS,JRF,RDOC,andCCK.DataCuration:AFB,JRF,RJO,MEP,EA,GCE,ATH,andDATC.Analyzedthedata:AFB,JRF,RJO,MEP,GCE,GB,andTAP.Providedclinicalsamplesand/orresources:LCM,MJLS,RDOC,FZD,MRP,LACJ,ECMM,LMRP,RFOF,BALF,andGLW.Writing–OriginalDraftPreparation:AFB, JRF,RJO,MEP,TAP,andNDG.Writing–Review&Editing:AFB,RFOF,TAP,GLW,andNDG.Supervision:GB,RFOF,TAP,BALF,GLW,andNDG.

AcknowledgementsWeacknowledgemembersoftheGrubaughLab,S.Taylor,andP.Jackfortheirongoingdiscussionsaboutthismanuscript.ThisworkwasfundedbytheHetchAwardprovidedbytheYaleInstituteforGlobalHealth(NDG),theInterneFondsenKULeuven/InternalFundsKULeuvenundergrantagreementC14/18/094(GB),andtheResearchFoundation–Flanders (‘Fonds voorWetenschappelijkOnderzoek–Vlaanderen’,G0E1420N;GB).

SupplementalInformationTableS1.DENV-1andDENV-2genomessequencedinthisstudy.(Excel)

TableS2.Parameterrangesfor𝛾𝑭and𝛾𝑺usedinestimatingforceofinfection.(pdf)

TableS3.PriorsforIndexPEstimates.(pdf)

TableS4.PrimersforDENV-1amplicon-basedsequencing.(Excel)

FigureS1.ZikacasesinBrazilperstate,2016-2018.(pdf)

FigureS2.RankingofForceofInfectionestimates.(pdf)

FigureS3.Probabilityofdenguefever(left)orseveredengue(right)conditionalonDENVinfection.

FigureS4.ProportionofpopulationssusceptibletoDENV.(pdf)

FigureS5.GenomecoverageofDENV-1andDENV-2samplessequencedfromFTAfilterpapercards.(pdf)

FigureS6.Root-to-tipanalysesofDENV-1andDENV-2genomesusedinphylogeneticanalyses.(pdf)

FigureS7.MaximumLikelihoodphylogeographicreconstructionofDENV-1evolutionintheAmericasusingenvelopesequences.(pdf)

FigureS8.MaximumLikelihoodphylogeographicreconstructionofDENV-2evolutionintheAmericasusingenvelopesequences.(pdf)



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TableS2.Parameterrangesfor𝛾𝑭and𝛾𝑺usedinestimatingforceofinfection.Themidpointsof𝛾𝑭weretakenfromPerkinsetal.76,andthemidpointsof𝛾𝑺weretakenfromFlascheetal.77.Minimumandmaximumvaluesoftherangeexploredare50%lowerandhigher,respectively,thanthemidpoint.

Parameter Minimum Midpoint Maximum

𝛾,D 0.09 0.18 0.36

𝛾,L 0.12 0.24 0.48

𝛾,NO 0.07 0.14 0.28

𝛾6D 0.055 0.111 0.222

𝛾6L 0.105 0.209 0.418

𝛾6NO 0.026 0.052 0.104



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TableS3.PriorsforIndexPEstimates

Parameter Priordistribution Sources

HumanIncubationPeriod Gaussian(mean=5,SD=1) 78–80

HumanInfectiousPeriod Gaussian(mean=5,SD=1) 78–80

HumanLifeExpectancy Gaussian(mean=73,SD=2) 81

Transmission probability (human tomosquito)

Gaussian (mean = 0.5, SD =0.01)

37

MosquitoBitingRate Gaussian (mean = 0.25, SD =0.05)

82,83

ExtrinsicIncubationPeriod Gaussian(mean=7,SD=2) 79,84,85

MosquitoLifeExpectancy Gaussian(mean=14,SD=3) 86,87



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FigureS1.ZikacasesinBrazilperstate,2016-2018.MoststatesexperiencedapeakinZikacasesbetweenFebruaryandJuly2016.



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FigureS2.RankingofForceofInfectionestimates.Ranking100maximumlikelihoodestimatesofForceofInfection(FOI)foreachregioninBrazil,forthetworecentyearsoflowdengueincidence(2017-2018).



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FigureS3.Probabilityofdenguefever(left)orseveredengue(right)conditionalonDENVinfection.EstimatesarepresentedpergeographicregioninBrazil,from2002to2019.



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FigureS4.ProportionofpopulationssusceptibletoDENV.AnnualproportionsofsusceptiblepopulationpergeographicregioninBrazil,from2002to2019.



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FigureS5.GenomecoverageofDENV-1andDENV-2samplessequencedfromFTAfilterpapercards.Dotplot showing thepercentageof thegenomecoveredby>10Xdepthby theoverallproportionof readsaligningtotheDENVgenomegenerated.Dashedlinerepresentsa70%genomecoveragethreshold.



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FigureS6.Root-to-tipanalysesofDENV-1andDENV-2genomesusedinphylogeneticanalyses.TheseplotswereobtainedusingTempEst,usingMLphylogeniesobtainedfromcompletegenomesof(A)DENV-1(n=458)and (B)DENV-2 (n=700).They show the correlationbetween the collection time (years)and thegeneticdivergence(substitutionspersite)fromtherootofthetree(MostRecentCommonAncestors,MRCA)tothetips(sampledgenomes).Thesloperepresentstheevolutionaryrate:8.47x10-4substitutions/site/yearforDENV-1;and1x10-3substitutions/site/yearforDENV-2.Allthenewlysequencedgenomesgeneratedinthisstudyfittheexpectedmolecularclockofvirusesfromtheirserotypes.



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FigureS7.Maximum-likelihoodphylogeographicreconstructionofDENV-1evolutionintheAmericasusingenvelopesequences.Atotalof1250envelopesequenceswereincludedinthisanalysis(newgenomeshighlighted with asterisks), performed using the augur pipeline from Nextstrain. Data visualization wasobtainedusingbaltic.py.Aninteractiveversionofthisphylogeographicreconstructionandmetadatacanbefoundathttps://nextstrain.org/community/grubaughlab/DENV-genomics/DENV1-Brazil.



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FigureS8.Maximum-likelihoodphylogeographicreconstructionofDENV-2evolutionintheAmericasusingenvelopesequences.Atotalof1202envelopesequenceswereincludedinthisanalysis(newgenomeshighlighted with asterisks), performed using the augur pipeline from Nextstrain. Data visualization wasobtainedusingbaltic.py.Aninteractiveversionofthisphylogeographicreconstructionandmetadatacanbefoundathttps://nextstrain.org/community/grubaughlab/DENV-genomics/DENV2-Brazil.

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