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ResearchReport
ALEXDEMARSH,PEDRONASCIMENTODELIMA,CASSIDYNELSON,JAVIERROJASAGUILERA,NATHANDUARTE,SELLANEVO,HENRYH.WILLIS
Strategiesto
ImproveDetection
ofNovelPandemic
Pathogens
CostVersusDetectionPerformanceforPromising
Pathogen-AgnosticDetectionWorkflows
RR-A3704-1
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AboutThisResearchReport
iii
Thepossibilityofapandemiccausedbyanovelpathogenmotivatesthedevelopmentand
deploymentofbiosurveillancesystemscapableofrapidlyrecognizingnovelthreats.Toinformdecisionsthatenablethenextgenerationofbiosurveillancesystemstorapidlydetectoutbreaksofnovelpathogens,ourteamevaluatedthecostanddetectionperformanceofthreepromising
pathogen-agnosticdetectionstrategies.Thesestrategiesemployedcombinationsofnovel
detectiontechnologiesinanidealizedsettingofdeploymentatmilitarybasesupportedbya
dedicatedmedicalfacility.Thisreportpresentsthetechnologiesandsystemsevaluatedand
detailstheresultsofasimulationstudydesignedtoestimatethetotalsystemcostversusits
detectionperformance,asmeasuredbytheproportionofpopulationinfectedatthetimeofthe
detectionandthetimefromemergencetodetection.Givenourfocusonearlydetection,this
analysisdoesnotprovidecomprehensivecosteffectivenessofthesesystemsasouranalysisdoesnotincludeactions,costs,andoutcomesfollowingdetectionofadiseaseoutbreak,suchascostsofdiseasedeathsandillnessorthecostsandeffectivenessofpandemicresponse.Theresultswillbeofinteresttodecisionmakersconsideringdeployingsuchasystemandthemethodscan
informanalysisofothertypesofbiosurveillancesystemstoserveotherpopulationsandcommunities.
CenteronAI,Security,andTechnology
RANDGlobalandEmergingRisksisadivisionofRANDthatdeliversrigorousand
objectivepublicpolicyresearchonthemostconsequentialchallengestocivilizationandglobalsecurity.Thisworkwasundertakenbythedivision’sCenteronAI,Security,andTechnology,
whichaimstoexaminetheopportunitiesandrisksofrapidtechnologicalchange,focusingon
artificialintelligence,security,andbiotechnology.Formoreinformation,contact
cast@
.
Funding
ThisresearchwasindependentlyinitiatedandconductedwithintheCenteronAI,Security,andTechnologyusingincomefromoperationsandgiftsandgrantsfromphilanthropic
supporters.Acompletelistofdonorsandfundersisavailableat
/CAST
.RANDclients,donors,andgrantorshavenoinfluenceoverresearchfindingsorrecommendations.
Acknowledgments
TheauthorsthankToddHelmus(RAND)forextensiveguidanceonanearlyversionofthisreport,andLisaColabella(RAND)forhersignificantcontributiontocostanalysis.Wefurther
iv
thankForrestCrawford(RAND)andJacobSwett(BlueprintBiosecurity)forhelpfulfeedback
throughout,andCaseyAveggio(RAND)forsupport.WealsothankCharlesChiu(UniversityofCalifornia,SanFrancisco)andRaffaeleVardavas(RAND)fortheircarefulandconstructive
review.
Summary
v
Detectingnovelpathogensisasignificantchallengeforbiosurveillancesystems,inpart
becausetheyrelyonpathogen-specificdetectiontechnologies.Decisionmakersplanningto
improvebiosurveillancesystemsusingpathogenagnostictechnologieslackevidenceontheirexpectedcostsandtheexpecteddetectionperformanceofalternativesurveillancesystem
designs.Investmentinimprovedbiosurveillancesystemsislimitedbyalackofclarityoncostversusperformance,aswellascompleximplementationchoices.
Approach
Thisreportintroducesamodelofthreebiosurveillancestrategies,referredtoasSyndromic,Wearable,andEnvironmental.Eachoftheseisapathogen-agnosticworkflowdesignedtodetectnovelthreatsviametagenomicnext-generationsequencing(mNGS).TheSyndromicand
Wearablestrategiesareinitiatedbyasignalfromsymptomaticorphysiologicalsensors
(respectively),whiletheEnvironmentalstrategyrunscontinuouslyandisintensified
responsivelybasedonexternalintelligencefromevent-basedsurveillance.Allstrategiesaredescribedfullyinthemaintext.First,weparameterizethismodeltoemulatethedetectionofwildtypeSARS-Cov-2.Then,weexplorehowchangesinpathogencharacteristicsand
technologyperformancechangekeydetectionandcostmeasures.Weinformourmodelwithparametersderivedfromtheliterature,andpubliclyavailableinformationonfixed,operating,andvariablecostsofdiseasesurveillanceactivities.
Thisreportprovidesinsightintothetradeoffsinherenttothedesignofbiosurveillance
systemsbysimulatingthreealternativestrategies.Ourmodelingapproachrequiresasetof
assumptionsaboutthepathogenbeingdetected(i.e.,transmissibilityanddiseaseprogression),
thedetectiontechnology(i.e.,sensitivityofalternativedetectionsystems)andhowitwouldbe
usedinareal-worldsetting.Theseassumptionsaredocumentedinourmainreportandits
technicalappendix.Thissimplifiedsettingandtreatmentofstrategiesasdiscretechoicesis
intendedtocapturekeyfeaturesofadeployedmilitarypopulationandprovideroughcostversusperformanceanalysisasoneinputforchoosinganovelsurveillancesystem.Acrossallscenarios,weassumetheexistenceofabaselinebiomedicalcapability,includingaccesstostandard
diagnostics,andbasicoutbreakinvestigationprocedures.Areal-worldimplementationwouldbuildonthisexistinginfrastructure,andlikelydeploythestrategiesconsideredherein
combinationratherthanatomically.
vi
KeyFindings
•TheEnvironmentalstrategyaffordedthelargestimprovementsindetectionperformanceinourbase-casescenario,followedbythewearablestrategy.
•Thesuperiorityoftheenvironmentalandwearablestrategiesoverthesyndromicstrategydegradesinscenarioswherethediseasehashightransmissibility,theproportionof
individualswhoareasymptomaticislowandwhenthediseasehasafastlatentperiod.
Recommendations
•Alimiteddeploymentwouldallowoperatingcoststobeestimatedwithmoreprecision,provideanopportunitytocollectlogisticalandoperationaldata,estimatedetection
performanceunderreal-worldconditions,andexploredatafusionwiththelargerbiosurveillanceenterprise.
•Thereissignificantuncertaintyinthereal-worldperformanceofnext-generation
sequencingtechnologies,whichcouldbegreatlyreducedviaalimiteddeploymentofoneofthestrategiesexploredinthisreport,oracombinationthereof.
Contents
vii
AboutThisResearchReport iii
Summary v
FiguresandTables viii
StrategiestoImproveDetectionofNovelPandemicPathogens:CostVersusDetection
PerformanceforPromisingPathogen-AgnosticDetectionWorkflows 1
Background 1
ThreeTechnologiesAssessedinThisStudy 2
Methods 3
Results 6
DetectionPerformanceandCostsVersusPathogenLatencyPeriods 8
Discussion 10
AppendixA.AssessedStrategies 12
AppendixB.SimulationModel 14
Abbreviations 28
References 29
AbouttheAuthors 33
FiguresandTables
viii
Figures
Figure1.DetectionPerformanceandCostwithVaryingReproductionNumbers 8
Figure2.DetectionPerformanceandCostwithVaryingLatentPeriod 9
FigureA.1.ConceptualIllustrationofDetectionstrategies 13
FigureB.1.CompartmentModelStructure 14
Tables
Table1.PerformanceofSurveillanceStrategiesinBase-CaseScenario 7
TableB.1.TransmissionModelParameters 16
TableB.2.SyndromicStrategyParameters 17
TableB.3.Wearablesstrategyparameters 19
TableB.4.EnvironmentalStrategyParameters 21
TableB.5.CostEstimatesfortheSyndromicStrategyperFacility 23
TableB.6.CostEstimatesfortheWearablesStrategyperFacility 24
TableB.7.CostEstimatesfortheEnvironmentalStrategyperFacility 25
TableB.8.SyndromicSurveillancePerformanceinScenarioDiscoveryAnalysis 25
TableB.9.PRIMBoxesforSyndromicDetectionWithin15DaysofWearable 26
TableB.10.PRIMBoxesforSyndromicDetectionWithin15DaysofEnvironmental 26
TableB.11.CARTClassificationPerformanceforRelativeDetection 26
TableB.12.ParameterImportanceRankingforDetectionPerformance(RandomForest) 27
1
StrategiestoImproveDetectionofNovelPandemicPathogens:CostVersusDetectionPerformanceforPromisingPathogen-
AgnosticDetectionWorkflows
Background
Thepossibilityofapandemiccausedbyanovelpathogenmotivatesthedevelopmentanddeploymentofbiosurveillancesystemscapableofrapidlyrecognizingnovelthreats.Pandemicscanbeinitiatedbyanaturallyemergingzoonosis,alaboratoryorresearchaccident,or
deliberatelyreleased.Recognizingthesignificanceoftheearliestcasesinanascentepidemicisdifficultforexistingbiosurveillancesystems,evenforfamiliarpathogens.Thechallengeis
significantlygreaterfornovelpathogensbecausepathogen-specificdetectiontechnologies
requireasignificanttimeinvestmentbeforetheycanbeadaptedtoanewthreat(Mortonetal.,2024).Thislaghashistoricallybeenovercomeviasyndromicsurveillance,whichentails
analyzingclustersofsymptomreportswithoutrequiringspecificdiagnosis(Henning,2004).
Still,anewoutbreakmaynotbesuspecteduntilmanyseverelyillcasespresenttoahealthservice,bywhichstageseveralhundredorthousandsmorecouldhavebeeninfected.
However,evenwhenrobustmonitoringandsyndromicsurveillancesystemsareinplace,
detectingemergingpathogenoutbreakshashistoricallyentailedadditionaldelays.Inaglobal
analysisofoutbreakreportsinvolvingbothknownandunknownemergingpathogens,the
mediantimebetweenoutbreakstartanddiscoverywas20days,withlaboratoryconfirmation
takingamedianof36days(Klubergetal.,2016).Deliberatelyreleasedengineeredagents
intendedtoevadecurrentsurveillancecouldpotentiallyhaveevenlongertime-to-detectionusingcurrentsystems.
Newclinicalandmoleculartestingtechnologiescanbeintegratedintobiosurveillance
systemstoprovideearlywarningofnascentepidemics,andifcoupledwithrobustresponse
measurescouldreducetheprobabilityofdevelopingintopandemics.Newdetectiontechnologiesareatvariousstagesoftechnologyreadiness.Somearecommerciallyavailableandwidelyused,suchasmultiplexPCRandsimilarbroad-scopemoleculartestsforclinicalsamples.Consumerinnovationsarecreatingnewusesandapplicationssuchaswearablebiometricsand
physiologicalsensors.Otheremergingtechnologiesareinearly-stageadoptionatspecializedlaboratories,suchaspathogen-agnosticmetagenomicanalysisofclinicalandenvironmental
samples.Researchsuggestspromiseinincorporatingpathogen-agnostictoolsinto
biosurveillance(Bassietal.,2022;Bohletal.,2022;Dengetal.,2020;Gardy&Loman,2018;Gauthieretal.,2023;Govenderetal.,2021;Milleretal.,2013;Mohsinetal.,
2021).Implementingthesetechnologiesinreal-worldbiosurveillancesystemspresentscost-
2
effectivenesstradeoffs,yettheresearchonthecost-effectivenessofthosesystemsisscant.cost-effectivenesstradeoffs,yettheresearchonthecost-effectivenessofthosesystemsisscant.
Toinformdecisionsthatenablethenextgenerationofbiosurveillancesystemstorapidly
detectoutbreaksofnovelpathogens,ourteamevaluatedthecostanddetectionperformanceofthreepromisingpathogen-agnosticdetectionstrategiesemployingnoveldetectiontechnologies.Thespecificidealizedsettingforthisanalysisisdeploymentatmilitarybasesupportedbya
dedicatedmedicalfacility.Thissitewasselectedbecausetwocharacteristicsmakeita
compellingsiteforapilotdeploymentofsuchasystem.First,thesiteinvolvesawell
characterized“closed”populationthatisreasonablyself-contained,whichsignificantly
simplifiesanalysiswhilestillprovidingreal-worldrelevance.Second,inthiscontext,the
militaryhasbroadauthoritiestoimplementnovelbiosurveillancesystems,andatrackrecordofsignificantinvestmentinnoveltechnologiestoprotectthewarfighter.Narrativesofthethree
strategiesareprovidedinAppendixAanddescribedinmoredetailinthefollowingsectionsofthisreport.
Thisreportpresentsthetechnologiesandsystemsevaluatedanddetailstheresultsofa
simulationstudydesignedtoestimatethetotalsysteminstallmentandoperatingcostversus
detectionperformanceforthesesystems.Theanalysiswasnotintendedtoprovide
comprehensivecosteffectivenessestimatesofthesesystems,anddoesnotincludeactions,costs,andoutcomesfollowingdetectionofadiseaseoutbreak.Theresultshelpinformdecisionmakersinterestedindeployingsuchasysteminaspecificlocationofthecoststheywouldexpectto
incur,andhowthesecostsrelatetodetectionoutcomes.
ThreeTechnologiesAssessedinThisStudy
Wedecidedtofocusoncomplementarytechnologieswhichcanbedeployedincombinationfornovelpathogendetection.Thesetechnologieswerechosenduetohavingoverlappingbut
distinctcharacteristics(cost,easeofdeployment,technologyreadiness,etc),collectivelyintendedtosupport“pathogenagnostic”workflows.
Thethreetechnologieschosenwerewearablesphysiologicalsensors(Wearables),multiplexPolymeraseChainReaction(mPCR),andmetagenomicNext-GenerationSequencing(mNGS).Respectively,thesetechnologiesprovidei)continuoussyndromicmonitoringofentire
populations,ii)broadbutpathogen-specificmoleculardetection,andiii)pathogenagnosticdetectionandrichthreatcharacterization.Eachisdescribedinmoredetailbelow.
WearablePhysiologicalSensors
Wearablesarecontinuouslywornphysiologicalsensorsthatcancomplementtraditional
diseasesurveillancesystemsbycontinuouslymonitoringphysiologicalparameterssuchasheartrate,bodytemperature,sleeppatterns,andbloodoxygenlevels(Kimetal.,2019).Subtle
3
deviationsfromnormalpatternscouldindicatetheonsetofaninfectionbeforephysicalsymptomsmanifest,andwellbeforepresentationatahealthcarefacility.
MultiplexPolymeraseChainReaction
mPCRpanelsscreenasinglesampleagainstavarietyofknownthreats,allowingforbroaddiagnosesundirectedbythepatient’ssymptoms(Wittweretal.,2001).Forourpurposesinthisanalysis,mPCRpanelsallow“rulingout”ofknown,commoncausesofillness,whichreduces
thenumberofsamplesreferredforwardforpathogen-agnosticmetagenomicsequencing,andhastheaddedadvantageofnotrequiringsignificantmarginalequipmentcosts.
MetagenomicSequencing
mNGScanbeusedtodetectanovelpathogenwithoutpriorknowledgeofitsgenomeand
demonstratessignificantpromiseinitsutilityasapathogen-agnosticsurveillancetool.mNGScouldalsoreducethetimebetweennovelpathogendiscoveryandgeneticcharacterization,
whichmayacceleratethedevelopmentanddeploymentofcountermeasuresthatrequiregenomeinformation.TherehavebeencallsforincorporatingmNGSintoglobalsurveillancefornew
outbreakdetectionandreducingthetimefromdiscoverytopathogencharacterization(Chiu&Miller,2019;Gardy&Loman,2018;Milleretal.,2013).
Methods
Ourbase-casescenariosimulatedanoutbreakofapreviouslyunknownairbornepathogensimilartoSARS-Cov-2spreadingperson-to-personinaclosedpopulation,beginningwitha
singleinfectedindividual.Thisscenariorepresentsanovelrespiratorypathogenwithpandemicpotential,spreadingthroughapopulationofdeployedmilitarypersonnel.
TechnicaldetailsofourepidemicsimulationcanbefoundinAppendixB(seeTransmissionModelsection,andAppendixBTable1).Briefly,weassumeeachhealthcarefacilityserveda
closedpopulationof1000susceptibleindividuals.Transmissionisexclusivelyperson-to-personwithapre-symptomaticperiodduringwhichaninfectedpersoncaninfectothers.Further,someinfectedindividualscaninfectotherswhileremainingasymptomatic.Baselineestimatesfor
parametersinthismodelreflectingcharacteristicsofthedisease,population,andtechnologies
wereidentifiedfromliteratureandexpertengagement.Therangeofvaluesused,nominalvalues,andtheirsourcesarepresentedinAppendixB.
ThenominalvalueofeachparameterismeanttorepresentapandemiccausedbyapathogensimilartowildtypeSARS-Cov-2,whereassensitivityanalysesevaluatetheperformanceofthesystemsacrossawidesetofscenariosrepresentingpathogenswithdifferenttransmissibilityandalternativeassumptionsabouttechnologyperformance.
Weassessedthreesurveillancestrategies,eachofwhichcombinedtraditionalandnoveldetectiontechnologiesinalogicalorder.Followingstandardpracticetoincreasecost-
4
effectiveness,weusedlowercost-per-usetechnologyforinitialscreeningandreservedhighercost-per-usetechnologyatalaterstageforsamplesthatweremorelikelytocontainanovel
pathogen.Thiswasintendedtomakeeachstrategyindependentlyascost-effectiveaspossiblewhileallowingcomparisonsofglobalcost-effectivenessacrossstrategiesforarangeofthreatscenarios,plausiblevaluesforuncertainquantities,andotherimplementationchoices.
Threetypesofcosts—fixedupfrontcostofinstallation,ongoingoperatingcost,andper-testvariablecost—wereestimatedthroughi)peer-reviewedliteratureincludingpublisheddatafromprioranalyses,ii)consultationswiththeauthorsofthesestudies,andiii)publiclyavailable
informationfrommanufacturers.DetailsoncostsandsourcesareprovidedinAppendixB.
SurveillanceStrategies
Toevaluatecost-effectivenessinarealisticdeploymentsetting,wheredetectiontechnologiesareunlikelytobeusedinisolation,weconsideredthree“strategies”fordetectingnovel
pathogens.Thesearebrieflydescribedbelow,anddetaileddescriptionsofeachstrategyare
providedinAppendixA.Theproportionofindividualsreferredtothenextstageofeachstrategywasvariedthrougharangeofplausiblevalues,asdetailedinAppendixB.
Syndromic
AfractionofsymptomaticindividualswhopresenttoahealthcarefacilityarefirstinvestigatedbyanmPCRpanel,withaproportionoftheremainingunexplainedsymptomaticindividuals
referredformNGS.TheSyndromicstrategymostcloselymirrorscurrentlyusedbiosurveillanceearlywarningsystems,withtheadditionofsystematicthreatcharacterizationthroughpathogen-agnosticmNGStesting.
Wearable
Similarly,inthisstrategyafractionofindividualswhoreceiveanalertfromapassivewearablesensorarefirstscreenedagainstknownrespiratoryillnesscausesusinganmPCRpanel,anda
fractionofstill-unexplainedalertsarethenfurtherinvestigatedviasystematicpathogen-agnosticmNGStesting.
Environmental1
Inthisstrategy,sequencingofbothwastewatersamplesandswabsfromarandomsubsetofthepopulationoccursatabaselinelowfrequency,whichcanbeintensified(intermsoffrequency,
1NotethatwhiletheSyndromicandWearablestrategiesarestructurallysimilarandcanbedirectlycompared,theEnvironmentalstrategyincludestheadditionalelementofadaptiveintensificationinresponsetooutside
information.ThissomewhatlimitsthedirectcomparabilityoftheEnvironmentalstrategy,andfutureworkcouldexploretheconsequencesofincludingthiselementintheotherstrategiesorassesstheperformanceofan
Environmentalstrategywithoutthisfeature.Further,sincethisstrategydoesnottestbasedonsymptomologyitismorevulnerabletofalsepositiveresults.Forexample,itispossiblethatbothwastewatersitesandindividual
5
populationfraction,and/orsequencingdepth)inresponsetoanexternalsignalorwarning(e.g.fromanevent-basedsurveillancesystem).Concurrentsamplingofwastewaterandswabsallowsforcross-comparisonofresultsfromacombinedcommunitysource(i.e.,wastewater)and
individualsinthepopulation,allowingforcorroborationthatanovelsequencedetectedinwastewatercorrespondstoanovelhumanpathogen.
SurveillanceCosts
Weestimatedcapital,operating,andper-testexpendituresassociatedwitheachstrategy.Forallstrategiesweassumedthepre-existenceandavailabilityoftypicallaboratorycapabilitiesandthusdidnotincludeadditionalcostsforroutinematerialsandequipment(includingPCR
machinesandstandardrelatedconsumables).Capitalcostsincludedinvestmentsinsequencingmachines,wearabledevices,andpersonalprotectiveequipment(specifically,2protectivere-
usablesuitsforwastewatersamplingintheEnvironmentalstrategy,perfacility),whileoperatingcostsincludedlaborandfacilityexpenses.Variableper-testcostsassociatedwithmPCRand
mNGSincludedmPCRtestkits,sequencingpreparationandreagents,aswellasothernon-
standardconsumables.Thesecostestimateswerebasedonprevailingmarketratesfor
comparablegoodsandstandardlaboratoryprocedures.AmoredetaileddescriptionofthecostsanddatasourcesisprovidedinAppendixB(seeTablesB.5toB.7fordetailedcostinformation).
ScenarioDiscovery
Apriori,weexpecttheSyndromicsurveillancesystemtounderperformindetectionrelativetotheWearableandEnvironmentalStrategies.Yetitisuncleartheextenttowhichthisresult
willholdacrossawidesetofpotentialnewpathogensandtechnologyperformance
characteristics.Therefore,weuseaScenarioDiscoveryapproach(Bryant&Lempert,2010)toidentifyconditionsunderwhicheachstrategywouldfailtodetecttheoutbreak15daysbeforethesyndromicstrategywouldotherwisedetectit.Wefocusontimetodetectionasthekey
outcomeinthisanalysisbecauseearlydetectionisthemaingoalofthosesystems.
WeconstructaLatinhypercubesample(LHS)encompassingtheplausiblerangeofall
parameterstoinvestigateconditionsunderwhichsyndromicsurveillancedetectsoutbreaks
withincomparabletimeframestotheotherstrategies.Specifically,wefirstrunthethree
strategiesinabase-casescenarioaimedtorepresentthecharacteristicsofapathogensimilarlytoSARS-Cov-2.Becauseeachstrategyhasadifferentsetofparameters(TablesB2,B3andB4),itisinefficienttocreateonesamplevaryingallparameterssimultaneously.Therefore,wecreate
twosetsofparameters:onetocomparetheWearablesstrategytotheSyndromicstrategy
(parametersinTablesB1,B2andB3)andonetocomparetheEnvironmentalStrategytotheSyndromicstrategy(parametersinTablesB1,B2andB4).Then,foreachparameterset,we
samplescouldbecontaminatedbyanovelnon-humanvirus(e.g.acircovirus),whichcouldproduceafalsepositivesignalthatwouldrequirefurtherinvestigationtoascertainasnotassociatedwithhumandisease.
6
comparethetime-to-detectionoftheWearableortheEnvironmentalstrategytotheSyndromicsurveillancestrategy,computingthenumberofdaysof“earlywarning”ofeachstrategyrelativetoSyndromicsurveillance.Inotherwords,wecomputea“detectiontimelinessregret”—i.e.,thenumberofadditionaldaysthatitwouldtaketodetectapathogenifthesyndromicstrategywasusedinlieuoftheothertwoalternatives.
Wethenapplyscenariodiscoverymethodstocharacterize“latewarning”scenarios—i.e.,
conditionsunderwhichenvironmentalorwearablestrategiesfailedtodetecttheoutbreak15
daysbeforesyndromicsurveillance.Our“latewarning”scenariothereforeiscodedasabinaryoutcome:scenarioswheresyndromicsurveillancedetectswithin15daysofthealternative
strategyarelabeledas“latewarning”cases,whilescenarioswherethealternativedetectsmorethan15daysbeforesyndromicarecodedas“earlywarning”cases.Theindependentvariablescomprise27parametersspanningpathogencharacteristics(reproductionnumber,asymptomaticprevalence,latentandrecoveryperiodrates),surveillanceimplementationfactors(metagenomicsequencingprobabilities,clinicvisitrates,testingsensitivities),andtechnicalspecifications
(wastewaterdetectionthresholds,sequencingdepth,sensorperformance).
UsingthePatientRuleInductionMethod(PRIM),wecharacterizeparameterregionswheresyndromicdetectionoccurswithin15daysofalternativestrategies.Inaddition,wealsouse
ClassificationandRegressionTrees(CART)toidentifyregionsintheparameterspac
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