OPTIONS Optimizing Prevention Technology Introduction On...

OPTIONSOptimizingPreventionTechnologyIntroductionOnSchedulePrEPModelingGapAnalysis

JULY2016

OPTIONSisoneoffivecooperativeagreementsawardedbyUSAIDwithPEPFARfundingthroughRoundThreeoftheAnnualProgramStatement(APS)forMicrobicideResearch,Development,andIntroduction.ThefivecooperativeagreementsarealsoknowncollectivelyastheMicrobicideProductIntroductionInitiative(MPii).Thesefive-yearawardscontinueandexpandUSAID'ssupport,inpartnershipwithPEPFAR,formicrobicideintroductionandaccesswithadvancesinbiomedicaltechnologiesandnewapproachesforHIVprevention.

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ProvidetargetedsupporttohelpexpediteandsustainaccesstonewARV-basedHIVpreventionproductsincountriesandamongpopulationswheremostneeded.

KENYA

SOUTHAFRICA

ZIMBABWE

WhereWeWork

ConsortiumPartners

Objective

OptimizingPreventionTechnologyInnovationonSchedule

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Howwework• Oursupportisflexibleandisdesignedtoberesponsivetoglobal

regionalandnationalcountryprioritiesandplans

• Wehavestrongin-countrypartners,e.g.WitsRHI,PangaeaandLVCTHealth,withsignificantexperienceworkingonHIVpreventionintheSouthAfrica,Zimbabwe,andKenyacontexts

• Inadditiontolocalpartners,ourconsortiumisabletobringmulti-disciplinaryexpertisetotheefforttointroducefemale-controlledHIVpreventionproductsinsub-SaharanAfrica

• Wearetakingsignificantstepstoensurewedonotreplicateexistingorongoingwork– ourmissionistofillgapsandhelpanswerkeyquestionsasoutlinedbyglobalstakeholders,nationalgovernments,USAIDmissions,andotherkeylocalstakeholders

• OPTIONSisnotaservicedeliveryproject;weapplysystemsthinkingtosupportandaccelerateproductintroduction

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GapAnalysisMethodology• Literaturereview

• Phone/emailinterviewswiththemajorityofmodelinggroupsworkingintheHIVfieldtodeterminecurrentmodelingactivities

• Analysisincludesrecentlycompleted,ongoing,planned,orproposedPrEPmodeling

• CountryfocusisKenya,SouthAfrica,andZimbabwe

• Studiesorganizedbyresearchquestion,sub-population,andcountry

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ModelingLiteratureReviewMethodologyAim:ToidentifythescopeofthecompletedPrEPandmicrobicidemodelingaspartofanassessmenttoidentifycurrentmodelingneeds.Thisliteraturereviewdidnotattempttoassessthequalityoftheworkbutrathertoidentifytheworkandobtainabroadoverviewofthefindings.

• OPTIONScollectedatotalof64modelingstudies,reviewsandanalysesfocusedontheimpact,cost,cost-effectiveness,drugresistanceandotherparametersofbothPrEPandmicrobicides.Studypublicationdatesrangefrom2003to2016.Studytypesincludedmodelingonpublichealthimpactandcost- effectivenessaswellasreviewsofexistingmodelingwork.

• Ofthesestudies,46lookedatPrEP,16atmicrobicidesandoneatbothPrEPandmicrobicides.Ofthese,eightstudiesaremeta-analysesorreviewsfocusedonPrEPandlookatimpact,cost- effectivenessanddrugresistance.

• Theliteraturereviewwasconductedthroughpeerreviewedjournalandabstractsearchesusingkeyterms,thesnowballmethod,andminingofstudycollectionsfrominternalpartners.

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ModelingLiteratureReviewOverviewStudiesandreviewslookedatthefollowingparameters:Measures/includes Total PrEP Microbicide BothImpact 37 25 11 1Cost/cost-effectiveness 27 23 3 1Drugresistance 15 14 1 0

Studiesandreviewsspecificallyidentifiedthefollowingpopulations:Population Total PrEP Microbicide BothHeterosexualserodiscordantcouples

3 3 0 0

Femalesexworkers(FSW) 8 5 3 0Youngwomen 4 3 1Menwhohavesexwithmen(MSM)

15 12 3 0

YoungMSM 2 2 0 0

Studiesandreviewsfocusedonthefollowinggeographicareas:Region Total PrEP Microbicide BothEast,SouthandSouth-EastAsia 6 2 4 0NorthAmerica 8 7 1 0SouthAmericaandCaribbean 3 2 1 0Sub-SaharanAfrica 37 29 7 1EasternEuropeandCentralAsia 2 1 1 0

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ModelingLiteratureReviewOverview• PrEPhasbeenextensivelymodelled

• MajorityofstudiesfocusonSouthAfrica,withfewerfocusingonKenya,andasmallnumberfocusingonZimbabwe

• Healthimpactandcost-effectivenesstwomostcommonresearchquestionsaddressed

• Femalesexworkers(FSW),adolescentgirlsandyoungwomen(AGYW)andunspecifiedpopulationsmostcommonpopulationsstudied

• Moststudieslookingatcost/cost-effectivenessconcludedwhilePrEPcanconfersignificantbenefititrequiressubstantialexpenditure

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ModelingLiteratureReviewSummary• Mostmodelingstudieslookingatcostandcost-effectivenessconcluded

thatwhilePrEPcanconfersignificantbenefit,itrequiressubstantialexpenditure

• Severalstudiesfoundthatmaximalcost-effectivenessisachievedbyprovidingtreatmenttoagreaternumberofinfectedindividualsearlierratherthanprovidingPrEPtouninfectedindividuals.

• SomemodelingpredictedthatforPrEPtobemostcost-effectiveitshouldbeusedbeforetreatmentreachesasaturationlevelwhilenotingthatearlytreatmentalonecannotreduceHIVincidenceenough(Cremin,2013;Pretorius,2010;Supervie,2011)

1. Cremin,I.,etal.,Thenewroleofantiretrovirals incombinationHIVprevention:amathematicalmodellinganalysis. AIDS,2013.27(3):p.447-58.2. Pretorius,C.,etal.,Evaluatingthecost-effectivenessofpre-exposureprophylaxis(PrEP)anditsimpactonHIV-1transmissioninSouthAfrica.

PLoS One,2010.5(11):p.e13646.3. Supervie,V.,etal.,Modelingdynamicinteractionsbetweenpre-exposureprophylaxisinterventions&treatmentprograms:predictingHIV

transmission&resistance. Sci Rep,2011.1:p.185.

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ModelingQuestions• WhatisthetotalestimateddemandforPrEPwithineachkeypopulation(e.g.,AGYW,

MSM,FSW)?

• Whatistheprojectedhealthimpact(e.g.,HIVincidenceandprevalencereductions)ofaddingPrEPtothemixofcurrentHIVpreventionandtreatmentinterventions? IsitpossiblefornationalHIVprevalenceandincidencereductiontargetstobereachedwithoutinvestinginPrEP?

• WhatistheincrementalunitcostofdeliveringPrEPthroughexistingornewchannelstoreachkeypopulations?

• Whatistheprojectedincrementalcost-effectivenessratio(ICER)ofaddingPrEPforaspecifiedpopulationtothemixofcurrentHIVpreventionandtreatmentinterventions? IsPrEPforagivenpopulationcost-effectiverelativetointernationalstandards?

• Whatarethepotentialcostsavings ofdeliveringPrEPintermsoflowerARTcosts?

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Gapsinmodelingdata:Demand

Question Population

published(L),conducted(C),ongoing(O),planned(P),orproposed(M)work;numbersrefertorownumberofrelevantworksheet

Kenya SouthAfrica Zimbabwe othersub-SaharanAfrica

WhatisthetotalestimateddemandforPrEPwithineachkeypopulation(e.g.,AGYW,MSM,FSW)?

AGYWO12(uptakepredictionsfromDCE)

FSWO12(uptakepredictionsfromDCE)

Sero-discordantcouplesMSMIDU

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Question Population

published(L),conducted(C),ongoing(O),planned(P),orproposed(M)work;numbersrefertorownumberofrelevantworksheet

Kenya SouthAfrica Zimbabwe othersub-SaharanAfrica

Whatistheprojectedhealthimpact(e.g.,HIVincidenceandprevalencereductions)ofaddingPrEPtothemixofcurrentHIVpreventionandtreatmentinterventions? IsitpossiblefornationalHIVprevalenceandincidencereductiontargets tobereachedwithoutinvestinginPrEP?

AGYW M3,M5O12,C13,O14,O15,M19,O21,L44

O21,O24,L51

FSW C2,M3,M5,L18,L53

O11,O12,C13,O14,M19 O22

sero-discordantcouples

O3 L11,L39 O3(Uganda)

MSM M3,C2 P14,O16,M14IDU

unspecifiedP8,L16(PrEPwithincomboprevention),L53

P8,P8(cabotegravir),P20,L13,L15,L22,L23,L25,L29,L31,L33(women),L35,L44

P20,P23,O24

O27,O28,L17(global),L27(Zambia),L30(SSA),L31(Zambia),L38(Botswana),L57(SSA)

Gapsinmodelingdata:Impact

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Question Population

published(L),conducted(C),ongoing(O),planned(P),orproposed(M)work;numbersrefertorownumberofrelevantworksheet

Kenya SouthAfrica Zimbabwe othersub-SaharanAfrica

WhatistheincrementalunitcostofdeliveringPrEPthroughexistingornewchannelstoreachkeypopulations?

AGYW C6,O7 BMGFFSW L20,L21,C6,O7 O9 O22sero-discordantcouplesMSM C6,O7IDUunspecified P8 P8,C13

Whatistheprojectedincrementalcost-effectivenessratio(ICER) ofaddingPrEPforaspecifiedpopulationtothemixofcurrentHIVpreventionandtreatmentinterventions? IsPrEPforagivenpopulationcost-effectiverelativetointernationalstandards?

AGYW M5 C13,O14,M19,L7,L44FSW C2,M5,L18 O9,C13,O14,M19 O22

sero-discordantcouples L11,L39 L2 L2(Uganda),L10(Mozambique)

MSM C2 P14IDU

unspecified P8P8,P8(cabotegravir),L15,L22,L29,L33(women),L44

P23 O27,L27(Zambia),L30(SSA)

Whatarethepotentialcostsavings ofdeliveringPrEPintermsoflowerARTcosts?

AGYW M5 C13,O14,M19FSW C2,M5 C13,O14,M19 O22sero-discordantcouplesMSM C2 P14IDUunspecified P8 P8 P23 O27

Gapsinmodelingdata:Cost-effectiveness

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Gaps:OPTIONSmodelingquestionsWhatismissingfromthePrEPmodelingstudiesconductedtodateareanswerstothefollowingquestions,ofparticularrelevancetopolicymakers:

1. Aretherespecificsubpopulations*in[countryofinterest]forwhichprovidingPrEPmay:a) Providealargeadditionalepidemiological

impact,inadditiontotheexistingsuiteofpreventioninterventionsandscale-upofART?

b) Becost-effective?

2. Howdoesdifferentialuptakebydifferentsub-populationsmodifytheimpactprojections?a) WhichnewARV-basedpreventionoptionsbest

satisfyadolescentgirls’andyoungwomen’sownneeds(preferences)?

b) WhataretheriskprofilesandsociodemographiccharacteristicsofwomenwhopreferPrEP?

3. Doesitcostmoretoreachhigherrisksubgroupsofwomen?a) Howdoesthisaffectthecost-effectiveness

projections?

OncethepopulationsforPrEPprovisionhavebeendecideduponthroughdiscussionswithpolicymakers,donors,andprogramplanners,basedonthemodelingandotherconsiderations,thefollowingmodelingquestionswillneedtobeaddressedforprogramplanning:

4. HowmanypeoplewillrequirePrEPin[countryofinterest]in[timeframedefinedbypolicymakers]?

a) Nationaldemandprojectionswillbedisaggregatedbydistrict/county/province,riskgroup,andservicedeliverymodel

5. Howmuchwillitcost?

6. Whatwillbetheprojectedimpact?

*Subpopulationsmaybedefinedbyriskgroup,age,sex,geography,accesstootherhealthcareservices,andotherfactors.

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What’sneededtoanswerquestionsforpolicymakers?

• Country-specificprimarydataareneeded;inthecaseofriskgrouppopulationsize,epidemiology,andbehavior,thedatamayalreadybeavailablethroughexistingsources

• However,forPrEP-specificquestionsaboutuptake,adherence,costofdifferentservicedeliverymodelsandreachingdifferentsubpopulations,thedatawilllikelycomefromthedemonstrationprojectsandotherprimarydatacollection;theavailabilityofthesedatamaybealimitingfactorforthemodeling

• Inadditiontothedata,adetailedage-structuredmodelisneededtoassessthepotentialadditionalepidemiologicalimpactofprovidingspecificsubpopulationsofAGYWwithPrEPinthecontextofscale-upofantiretroviraltreatmentandvoluntarymedicalmalecircumcision

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What’sneededtoanswerquestionsforprogramplanning?• Toestimatequestionsofdemand,healthsystemsresourceutilizationandtotal

programcost,additionalinformationisneededregardingthecostofPrEPthroughdifferentdeliverychannelsfordifferentsubpopulationsineachcountry

– Mostofthesecostdatahavenotyetbeencollected,giventhatimplementationisstillintheearlystages,andimplementationstrategiesarestillbeingworkedoutinthecontextofthedemonstrationstudies

• Inaddition,informationneedstobecollectedaboutthesizeofspecificsubpopulations (e.g.,highestriskadolescentgirlsandyoungwomen,sexworkerswithdifferentbehavioralandriskcharacteristics)andaboutexistingandpossibleexpansioncapacityofthedeliverysystemsthatwouldbeutilizedforPrEP

• Ifthesedataareavailableorbecomeavailable,additionalmodelingcanbeconductedtoassistwithquantifyingdemandandprojectingtotalcostandimpactofagivenPrEPtargetingstrategy

Thank you

ThisprogramismadepossiblebythegenerousassistancefromtheAmericanpeoplethroughtheU.S.AgencyforInternationalDevelopment(USAID)inpartnershipwithPEPFARunderthetermsofCooperativeAgreementNo.AID-OAA-A-15-00035.The

contentsdonotnecessarilyreflecttheviewsofUSAIDortheUnitedStatesGovernment.