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Technicalappendix

Thehealthofnations:Strongerhealth,

strongereconomies

February2026

Number19,June2025

Tableofcontents

3

Estimatethehealthimprovementsfromscalingselectedhealthinterventions

10

Quantifytheeconomicbenefitofimprovedhealth

14

Estimatetheincrementalcostandeconomicreturn

Bibliography

19

ThisappendixoutlinesthemethodologyandkeyassumptionsunderlyingthePrioritizingHealthmodel,

whichassessestheglobaldiseaseburdenandmodelsthepotentialimpactofscalingprovencost-efectivehealthinterventionsonpopulation-levelhealthandtheglobaleconomy.

Thisanalysisrepresentsan“artofthepossible”approach,aimingtoestimatethepotentialbenefits

ofexpandingaccesstoprovenhealthinterventionsonaglobalscale.Whileitprovidesahigh-level

perspectiveontheopportunitiesandimpact,itisimportanttoacknowledgethatthereareinherent

limitationsinthedata,clinicalevidence,andassumptionsused.Furtherresearchinthisareawouldbevaluabletorefinetheestimates.

Themodelcomprisesthreemainanalyticalsteps:

—Estimatethehealthimprovementsfromscalingselectedhealthinterventions.

—Quantifytheeconomicbenefitofimprovedhealth.

—Estimatetheincrementalcostandeconomicreturn.

Estimatethehealthimprovementsfromscalingselectedhealthinterventions

Themodeladoptedabottom-upapproach,assessingindividualhealthconditionsindetailandestimating

thepotentialreductionindiseaseburdenachievablethroughthescale-upofspecificinterventions.It

encompassedapproximately90conditions,representingabout85percentofthetotalglobaldisease

burden,andincorporatedrisk-attributableburdenfromaround27riskfactors,whichtogetheraccounted

forroughly98percentofthetotalrisk-attributablediseaseburden.Fortheseconditions,potential

reductionsindiseaseburdenwereestimatedusingthenine-stepanalyticalapproachdescribedinExhibit1.

Fortheremainingconditions—constitutingtheresidual15percentoftheglobaldiseaseburden—anaverageimpactproportionwasapplied,derivedfromcomparableconditionswithinthesamediseasegroupor

categoryforwhichdetailedanalyseswereconducted.

1.Selectconditionsforin-depthanalysis

ThemodelusedtheInstituteforHealthMetricsandEvaluation(IHME)GlobalBurdenofDisease(GBD)

2021datasuiteastheanalyticalbaseline.ProjectionsoffuturediseaseburdenweredrawnfromIHME’s

forecastestimates,whicharebasedonacomprehensiveandsystematicallycuratedglobalhealthdatabase.Nevertheless,forecastsofdiseaseburdenareinherentlyuncertain,andunanticipatedhealthshocks,policychanges,orgeopoliticaleventsmaymateriallyafectfutureoutcomes.

WithintheGBDdataset,diseaseburdenisquantifiedusingdisability-adjustedlifeyears(DALYs)and

causesareorganizedinahierarchicalstructure:Level0aggregatesallcauses;Level1distinguishes

broadcausegroupingsofcommunicable,noncommunicable,andinjurycauses;Level2disaggregates

diseaseburdeninto22majordiseasegroups,includingcancers,cardiovasculardisorders,andmental

disorders;andLevels3and4compriseprogressivelymoredetailed,condition-specificclassifications

basedonclinicalandepidemiologicalsimilarity.1TheIHMEGBDdataset,comprising178Level3conditions,servedasthestartingpointforidentifyingleadinghealthconditionsforin-depthanalysis,collectively

accountingforapproximately80percentoftheglobaldiseaseburden(measuredinDALYs).Toensurecomprehensivecoverageofmajorhealthchallengesacrossgeographiesandpopulationsegments,theselectedconditionswerebenchmarkedagainstthetoptencausesofdisabilityandmortalityacross

1GlobalBurdenofDisease2021:FindingsfromtheGBD2021study,IHME,May16,2024.

Thehealthofnations:Strongerhealth,strongereconomies3

Thehealthofnations:Strongerhealth,strongereconomies4

Exhibit1

Therewereninekeystepstoestimatethehealthimpactofscalingaccesstoprovenhealthinterventions.

Perdiseaseimpactanalysis

AnalyticalstepDetaileddescriptionMainsources

Assessdiseaseburden

1.Selectconditionsforin-depthanalysis:Identifyasetofhealthconditionsthatcollectivelyaccountforapproximately85%ofthetotalglobaldiseaseburdenfordetailedmodelingandanalysis

2.Estimaterisk-attributableburden:Foreachcause–riskpairacross27riskfactors,estimatetherisk-attributablediseaseburden,adjustingforinterdependencies

betweenriskstoavoiddouble-counting

InstituteforHealthMetricsand

Evaluation(IHME)GlobalDisease

Burden(GDB)2021datasuite

Identifyhealth

interventionsand

researchimpactassumptions

3.Identifyandcategorizeinterventions:Reviewclinicalliteraturetoidentifycost-

efectiveandscalableinterventionswiththegreatestpotentialforimpact—coveringbothpreventiveinterventionsthatreducediseaseincidenceandtherapeutic

interventionsthataddressestablishedconditions

4.Estimateefectsizes:Foreachinterventionwithineachdiseasearea,determinetheefectivenessrelatedtomortalityandmorbidityreduction,drawingonthebestavailableclinicalevidence

5.Estimatethebaselineandtargetadoptionrates:Assessthepotentialfor

increasedadoptionofeachinterventionunderabest-practicescenario,accountingforfactorssuchasuptake,sustainedadherence,andimplementationfeasibility;

adjustestimatesbyincomearchetypetorelectinfrastructureandresourceconstraints

6.Estimateinterventionramp-uptimeline:Usinginsightsfromclinicalreviewsandexpertconsultations,estimatethetimerequiredtoreachfullimplementationand

impact,includinganydelaysininitialuptake

7.Defineinterventionsequence:Applyinterventionssequentially—startingwithenvironmentalandbehavioralinterventions,followedbymedicalpreventionandfinallytherapeuticinterventionsforestablisheddisease—eachactingonthe

remainingburdenaftertheprecedingcategoryhasbeenapplied

WHOguidelines,

DiseaseControl

Priorities,third

edition,and

international

agencies;systematicreviews(eg,

Cochrane),The

Lancet,andhigh-impactjournals

Calculateimpact

8.Calculatetheimpactonyearslivedwithdisability(YLDs),andyearsoflifelost

(YLLs),anddeaths:Estimatepotentialreductionsindeaths,YLDs,andYLLsby

incrementallyapplyingefectsizes,adoptionrates,andtimeadjustmentstobaselineIHMEdiseaseburdenprojectionsfrom2025to2050

Thesequentialsummationfollowstheformula:

Attributableburden×Efectsize×Additionaladoption×Timeadjustment

9.Estimateimpactonlifeexpectancyandhealth-adjustedlifeexpectancy(HALE):Usedeathsavertedtorecalculateabridgedlifetablesandestimategainsinlife

expectancy;dericeimprovementsinHALEbycombiningYLDsavertedwiththerevisedlifeexpectancyestimates

IHMEGBD2021datasuite

McKinsey&Company

regions,incomearchetypes,2andagegroups.Additionalconditionswereincludedwhereneededtoensurerepresentativeness.Thisprocessresultedinapreliminarylistof46conditions,presentedinExhibit2.

Eachconditiononthelistwasthenreviewedtodeterminewhetheritwasdefinedinawaythatenabledtheidentificationofproveninterventionsandtheestimationofpotentialimpactthroughincidencereduction,

2ThecountryincomearchetypeswerebasedonWorldBankincomeclassifications.

Thehealthofnations:Strongerhealth,strongereconomies5

Exhibit2

Alistof46diseasegroupswasincludedinthein-depthanalysis.

Shareofglobaldisability-adjustedlifeyears,2025,%

Ischemicheartdisease

Neonataldisorders

Stroke

Lowerrespiratoryinfections

Diabetesmellitus

Chronicobstructivepulmonarydisease

Lowbackpain

Roadinjuries

Diarrhealdiseases

Depressivedisorders

Othermusculoskeletaldisorders

Headachedisorders

Congenitalbirthdefects

Tracheal,bronchus,andlungcancer

Age-relatedandotherhearingloss

Cirrhosisandotherchronicliverdiseases

Malaria

Falls

Alzheimer’sdiseaseandotherdementias

Chronickidneydisease

Tuberculosis

Anxietydisorders

COVID-19

HIV/AIDS

Self-harm

Dietaryirondeficiency

Blindnessandvisionloss

Hypertensiveheartdisease

Gynecologicaldiseases

Interpersonalviolence

Colonandrectumcancer

Oraldisorders

Osteoarthritis

Stomachcancer

Breastcancer

Neckpain

Asthma

Alcoholusedisorders

Drugusedisorders

Upperdigestivesystemdiseases

Schizophrenia

Idiopathicepilepsy

Drowning

Esophagealcancer

Livercancer

Endocrine,metabolic,blood,andimmunedisorders

Additionalconditionsincluded

Source:GlobalBurdenofDisease,InstituteforHealthMetricsandEvaluation,2021(usedwithpermission,allrightsreserved);McKinseyHealthInstituteanalysis

McKinsey&Company

Thehealthofnations:Strongerhealth,strongereconomies6

severityreduction,orboth.Forcertainbroaddiseasecategories,moredetailedanalysisatalower

classificationlevelwasdeemednecessarytoimproveaccuracy.Insuchcases,Level3categorieswere

replacedwiththeircorrespondingLevel4diseaseclassifications.Thisrefinementwasappliedtoconditionssuchasdiabetesmellitus(assessedseparatelyastype1andtype2),stroke(ischemicstroke,intracerebral

hemorrhage,andsubarachnoidhemorrhage),headachedisorders(migraineandtension-type),blindnessandvisionloss(cataract,glaucoma,age-relatedmaculardegeneration,refractivedisorders,andnear-visionloss),anddrugusedisorders(includingcocaine,amphetamine,opioid,cannabis,andotherdrugusedisorders).

Followingtheseadjustments,thefinaldeep-diveanalysiscovered89diseases,withalldiseasegroupswellrepresented,coveringabout85percentofthetotalglobaldiseaseburden.

2.Estimaterisk-attributablediseaseburden

Forconditionsinwhichdiseaseburdenisattributabletospecificriskfactors(forexample,type2diabeteslinkedtohighBMIorischemicheartdiseaseassociatedwithhighbloodpressure),more-granularrisk-

attributablediseaseburdenestimateswereincorporatedintothemodel.Theanalysisincluded27risk

factorsspanningmetabolic,environmentaloroccupational,andbehavioralcategories,alignedwiththe

classificationsdefinedbytheIHMEGBDdataset.Collectively,theseriskfactorsaccountforapproximately98percentofthetotalrisk-attributablediseaseburden,enablingthetargetedapplicationofinterventionstoaddressspecificunderlyingrisks.

AccordingtotheIHMEriskburdendataset,mostconditionsareassociatedwithmultipleriskfactorsthatcontributejointlytotheoveralldiseaseburden.Theseriskfactorsareofteninterdependent—forinstance,metabolicriskssuchashighfastingplasmaglucoseandhighBMImayoverlapintheircontributionto

diseaseoutcomes.Topreventdoublecountingwhenestimatingthepotentialimpactofinterventions

aimedatreducingtheserisks,themodelappliedadeduplicationadjustment.Thisadjustmentallocated

proportionalburdenwithineachLevel1riskgroup—namely,metabolic,environmentaloroccupational,andbehavioralrisks—ensuringthattheaggregateburdenwasaccuratelyrepresentedwithoutoverestimation.

3.Identifyandcategorizeinterventions

Areviewofclinicalliteraturewasconductedtoidentifycost-efectiveandscalableinterventionswith

thegreatestpotentialforhealthimpact,includingbothpreventivemeasuresaimedatreducingdisease

incidenceandtherapeuticinterventionsaddressingestablisheddisease.Theobjectiveofthisprocesswastodeterminehigh-impactinterventionsthatcouldsubstantiallyreducediseaseburdenifimplementedmoreefectivelyandifaccessgapswereminimized.Sourcesusedfortheinterventionreviewincludedclinical

guidelines(fromarangeofnationalprofessionalbodies);WorldHealthOrganization(WHO)guidance;

theDiseaseControlPriorities,thirdedition(DCP-3);andotherinternationalhealthagencies—aswellasevidencefromsystematicreviews(forexample,Cochrane)andpeer-reviewedpublicationsinTheLancetandotherhigh-impactjournals.

Thissetofinterventionswasnotintendedtorepresentanexhaustivecatalogofallpossiblemeasures

availableinafullyresourcedhealthsystembutrathertorelectthosewiththestrongestevidencebaseandhighestimpactandscalabilitypotential.Intotal,themodelincorporatedabout300interventionsacrosstheanalyzedconditions.

Healthinterventionswerecategorizedintothreebroadgroups:

Population-levelprevention:

—Environmentalinterventions:Policiesandregulatorymeasures(forexample,alcoholtaxation)andplace-basedprograms(suchasschool-baseddrugprevention,needleandsyringeprograms,orworkplace

initiativesaddressinghigh-riskalcoholuse)

Thehealthofnations:Strongerhealth,strongereconomies7

Individual-levelprevention:

—Behavioralinterventions:Approachespromotingindividualbehaviorchange,includingsmoking-cessationsupportandweightmanagementthroughlifestylemodification

—Healthpromotionandpreventiveinterventions:Activitiesencompassingscreening,earlydetection,primarycare,andpreventivepharmacotherapy(forexample,antihypertensivesorGLP-1receptor

agonistsforobesity)

Therapeuticinterventions:

—Therapeuticinterventions:Measuressuchasspecializedcare(forexample,jointreplacementsurgery),pharmacologicaltreatment(suchasantibiotics),caremanagement,counselingandpsychotherapy(forexample,peersupportprogramsandtalkingtherapies),anddigitaltherapeutictools

4.Estimateefectsizes

Estimatesofinterventionefectivenesswereextractedfromsystematicreviewsand,ifnosystematic

reviewwasidentified,fromotherclinicalstudies.Efectivenesswasestimatedseparatelyformorbidityandmortality.Formorbidityreduction,themostappropriateavailableoutcomemeasurewasselected—for

example,changeinsymptomsseverity.Whereaninterventionwasonlyapplicabletoaproportionofthediseaseburden,suchasaspecificagegroup,efectestimateswereappliedonlytoappropriategroups.

Forexample,aschools-basedobesity-preventionprogramwasappliedonlytotheassociatedburden

inagegroupsfromfiveto19years.Efectivenesswasassumedtobeconsistentacrosscountryincome

archetypes.Theestimatesusedinthismodelwereintendedasaveragesacrossrelevantpatientpopulationsandmayvaryforspecificsubpopulationsinwaysnotconsideredinthemodel.

5.Estimatetargetadoptionrates

Themodelaimstoestimatetheincrementalimpactofscalingupaccesstoprovencost-efectivehealth

interventionsrelativetothecurrentbaseline.Adoptionassumptionswerederivedfromthediference

betweencurrentadoptionlevelsandaspirationaltargetadoptionlevels.Currentadoptionrateswere

estimatedforeachinterventionandcountryincomearchetypeusingthebestavailableevidence,reviewedandvalidatedbysubjectmatterexperts.

Twoscenariosweredevelopedtoestimatetargetadoptionrates:

—Aspirationalbest-practicescenario.Targetadoptionratesforeachinterventionwereestimatedbyaccountingforfactorssuchasuptake,sustainedadherence,andimplementationfeasibility.The

bestavailableevidencewasusedforeachintervention–diseasecombination,drawingonreal-world

exampleswheredataexisted.Wheredirectevidencewasunavailable,adoptionrateswereinferredfromanalogousinterventiontrendsovertimeandsubsequentlyreviewedwithdisease-areaexperts(Exhibit3).Estimateswerefurtheradjustedbyincomearchetypetorelectvariationsininfrastructureand

resourceavailability.

—Theoreticalmaximumscenario.Thisscenarioassumed100percenttargetadoptionforallinterventions,representingtheupperlimitofpotentialimpactachievablethroughexisting,proveninterventions.

Thepurposeofthisscenariowastoquantifytheresidualdiseaseburdenthatcouldnotbeaddressedwithoutfutureinnovationornewinterventiondevelopment.

Thehealthofnations:Strongerhealth,strongereconomies8

Exhibit3

Aspirationalbestpracticeadoptionassumptionswereusedwherecredibleevidencewasnotavailable.

Aspirationalbestpracticeadoptionswherecredible/preciseestimatesarenotavailable

Interventioncategory

Interventiontype

Aspirationaladoption

Rationale

Nationalpoliciesandregulations

100%

Assumespoliciesaredesignedtofurther

Population-level

(eg,roadsafetymeasures,alcohol

restrict/controlhighriskexposuresfrom

prevention

andtobaccocontrols)

baseline(current)position

(environmental

interventions)

Industrystandards(eg,

75%(low-incomecountries

Assumesvaryingbaseline(current)

occupationalexposurelimitsfor

[LIC]/lower-middle-

levelsofregulationandresourcingfor

knownpollutants)

incomecountries[LMIC]/

upper-middle-income

countries[UMIC]),100%(high-incomecountries[HIC])

enforcement/compliance

Individual-level

Vaccines

95%

Assumes95%targetadoptionunlessanotherstandardisproposedinclinical

prevention

(behavioraland

practiceguidelines

healthpreventionandpromotion

interventions)

Screening

75%

Assumes75%targetuptakeunlessanotherstandardisproposedin

screeningguidelines

Preventivemedicines(interventions

75%

Assumes75%targetadherenceacross

requiringprolongedadherence)

alleligiblegroups(includingcurrently

undiagnosedpatients)

GLP-1sforobesityand

37%(HIC),20%(UMIC),

Assumesadoptionrateseenforexisting

diabetesrisk

8%(LMIC),7%(LIC)

genericmedsusedincardiovascular

preventionby2050

Participatoryinterventions

60%

Assumes60%voluntary,regularparticipation

(requiringregularattendance

unlessevidencefoundsuggestinganother

overtime)

levelforspecificinterventionsdeliveredinline

withbestpractice

Therapeutic

Standardclinicalpractice

90%

Assumeshighlevelofadherenceto

(eg,routinesurgery,medicines

clinicalpracticeguidelinescanbe

foracutemanagement)

achievedovertime

Medicinesforchronicdisease

90%

Assumeshighlevelofdiagnosisand

management

adherencetoclinicalpracticeguidelines

canbeachievedovertime

Interventionswithhigh

83%(HIC),65%(UMIC),

Assumesinvestmentininfrastructure

infrastructureneeds(workforce,

49%(LMIC),42%(LIC)

overtimeisalignedtourbanizationratein

facilities(eg,complexsurgery)

2050(WorldBankestimates)

New/advancedinterventions

80%(withtimelagfor

Assumesinterventionscurrently

(eg,digitaltherapeutics,

implementation)

considerednew/advancedwillbecome

biologics,newmedtech)

standardclinicalpracticeby2050

McKinsey&Company

Thehealthofnations:Strongerhealth,strongereconomies9

6.Estimateinterventionramp-uptimeline

Expandingaccesstointerventionstakestime.Assumptionsaroundimplementationramp-uptimestoreachpeak(oraspirationaltarget)adoptionwerebuiltintothemodel,tailoredtodiferenttypesofintervention

andtoeachofthefourcountryincomearchetypes.Theseestimateswerebasedonreal-worldexamplesoftimetoimplementationindiferenthealthsystemcontexts,aswellasuniversalhealthcoveragetrends.Theanalysisutilizedans-shapedramp-upcurve,relectingaslowerinitialadoptionratefollowedbyacceleratedadoptionovertime,tobettersimulatereal-lifescenarios.

Iftherewasatimelagbetweenaccessinganinterventionandrealizingthehealthbenefitforaspecific

condition,thiswasalsoaccountedforthroughanadjustmenttotheramp-upcurve.Forexample,smoking-cessationsupportnotonlyhasimmediatebenefitsforsomeconditionsbutalsoreducestheriskof

developingotherconditionsoversubsequentdecades.

7.Defineinterventionsequence

Foreachdiseaseincludedintheanalysis,themodelquantifiedtheimpactofoneormorerelevant

interventions.Tomoreaccuratelyrelectreal-worldimplementation,theimpactofinterventionswas

calculatedsequentially.Thesequencewasdeterminedbyinterventiontype:environmentalandbehavioralinterventionswereappliedfirst,followedbyhealthpromotionandpreventivemeasures,andfinally

therapeuticinterventions.

Eachsubsequentintervention’spotentialimpactwasappliedonlytotheremainingdiseaseburdenafteraccountingforthereductionachievedbyprecedinginterventions.Theorderingofinterventionswithin

eachcategorywasdeterminedinconsultationwithclinicalexpertsintherelevantfields.Thissequencingapproachwasdesignedtoavoiddoublecountingofpotentialimpactsanddoesnotrepresentreal-worldclinicalpractice,wheremultipleinterventionsmaybeimplementedconcurrentlyandtreatmentorderis

determinedbyindividualpatientcircumstancesratherthanafixedsequence.

Thesequencingwasappliedwithintheburdenofeachcondition.Whereaninterventionwasrelevanttomorethanonecondition,thesequencingordervariedbyconditionasappropriate.

8.Calculatetheimpactonyearslivedwithdisability,yearsoflifelost,anddeaths

Themodelwasappliedtoestimatethepotentialreductioninglobaldiseaseburdenachievablethroughthescalingofprovenhealthinterventionsovera25-yearperiod.Acomprehensivebaselinedataset

wasgeneratedfortheyears2025to2050,incorporatingbothrisk-attributableandcause-specific

burdenestimatesforallconditionsincludedinscope,basedonIHMEGBDforecastestimates.This

datasetwasdisaggregatedbycountry,sex,andfive-yearagegroups,inalignmentwiththeprecedingmethodologicalsteps.

Healthinterventionsandtheircorrespondingefectswereimplementedsequentiallyovertime,beginningwiththoseaddressingmodifiableriskfactors,followedbypreventiveandtherapeuticinterventions.Eachsubsequentinterventionwasappliedonlytotheresidualdiseaseburdenremainingafteraccounting

forreductionsachievedbypriorinterventions.Interventionswereassignedtorelevantagegroupsandpopulationsegmentsbasedonepidemiologicalappropriatenessandavailableevidence.

Todeterminetheannualimpact,thebaselinediseaseburdenforeachpopulationsegmentwasmultipliedbytheinterventionefficacyrate,adjustedfortheincrementaladoptionpotentialandtheramp-upfactorcorrespondingtotheyear,interventiontype,andincomearchetypeofeachcountry.Thisprocessallowedfordynamic,time-sensitivemodelingofinterventionefectsundervaryingimplementationandresourceconditions.Thisprocedurewasconductedseparatelytoestimatereductionsinyearslivedwithdisability

Thehealthofnations:Strongerhealth,strongereconomies10

(YLDs),yearsoflifelost(YLLs),anddeaths.TheresultingestimatesforYLDsandYLLswerecombinedtocalculatethetotalchangeinDALYs,representingtheaggregateimprovementinpopulationhealthundereachmodeledscenario.

Thesequentialsummationofinterventionefectsfollowedtheformula:

Attributableburden×Efectsize×Additionaladoption×Timeadjustment

Finally,modeloutputswereextrapolatedtodiseasesnotincludedinthedetailedanalysis—representingapproximately15percentofthetotalglobaldiseaseburden—byassuminganaverageimpactproportionconsistentwithdiseaseswithinthesameLevel2categoryasdefinedintheIHMEGBDdataset.

9.Estimateimpactonlifeexpectancyandhealth-adjustedlifeexpectancy

Toestimatetheimpactofscalinghealthinterventionsonlifeexpectancy(LE)andhealth-adjustedlife

expectancy(HALE),themodelrecalculatedtheunderlyingabridgedlifetablesusingtheremainingdeathsandYLDpercapitaderivedfromthepreviousstepsafterscalingprovenhealthinterventions.Comparingpre-andpost-interventionvaluesforLEandHALEresultedinadeterminationoftheincreaseinLEand

HALEthatwasduetotheappliedhealthinterventions.3

Allmodelinputsandoutputswerereviewedbyclinicalexpertsspecializinginrelevantdiseaseareas.Theseexpertsevaluatedtheselectionofinterventions,theassumptionsonpotentialuptake,thesequencingof

implementation,andtheestimatedhealthimpactsacrossdiferentcountryincomegroups.Thisreview

processensuredtheappropriatenessofevidenceinterpretationandprovidedanopportunitytotest

assumptionswheredatawerelimited.Theexpertreviewofmodeloutputs,suchasprojectedreductionsindiseaseburden,wasalsousedtovalidateandrefinethefindings.

Themodelresultswerefurthercomparedwithpublishedsourcestoassessconsistencywithexternal

evidence.Findingsforthetop26conditionsweretriangulatedwithglobalmultiyeardiseasereductiontargetssetbymajorinternationalagencies,suchasWHOandtheUnitedNations(UN).Anydiferencesobservedwereprimarilyattributabletovariationsinadoptionassumptionsormodelingparametersacrossstudies.

Quantifytheeconomicbenefitofimprovedhealth

Toquantifytheeconomicimpactofreducingtheglobaldiseaseburdenthroughthescale-upofproven

healthinterventions,themodelestimatedsupply-sidegainsassociatedwithalarger,healthier,andmore

productiveworkforce.Economicbenefitsarisingfromimprovedpopulationhealthwereprojectedfortheperiodfrom2025to2050andexpressedasincrementalGDPgains,basedonestimatedreductionsin

diseaseburden.GDPprovidesaconsistentandwidelyusedframeworkforassessingmacroeconomic

impactsofhealthimprovements;however,itdoesnotcapturealldimensionsofsocietalwell-being.In

particular,itundervaluesunpaidcaregivingandhouseholdwork—activitiesdisproportionatelyundertaken

3HaidongWangetal.,“Globalage-sex-specificfertility,mortality,healthylifeexpectancy(HALE),andpopulationestimatesin204countriesandterritories,1950–2019:AcomprehensivedemographicanalysisfortheGlobalBurdenofDiseaseStudy2019,”TheLancet,October

2020,Volume396,Number10258;abridgedlifetabledefinitionsbyM.Greenwood,“Discussiononthevalueoflife-tablesinstatistical

research,”JournaloftheRoyalStatisticalSociety,June1922,Volume85,Number4;andChinLongChiang,TheLifeTableandItsApplication,KriegerPublishingCompany,1984.