Long-term Projections of the Cost of Treatment Under Various Scenarios – Opportunities for Efficiency and Effectiveness? Arin Dutta, Cathy Barker, and Ashley Kallarakal July 19/20, 2014 DRAFT : DO NOT CITE

1. Projecting and costing global HIV treatment  Number on treatment a)Current vs. WHO 2013 need for ARVs b)Scale-up of programmatic coverage c)Migration to 2 nd line treatment  Cost of HIV treatment  Funding gap analysis for HIV treatment 2. Emerging Themes: E 2 in HIV Treatment 3. HPP E 2 analyses  Insights from Kenya, Tanzania, and Mozambique Outline

UNAIDS 2014 “Ambitious Treatment Targets: Writing the final chapter of the AIDS epidemic”  Critical intervention in the response: preventing premature mortality and new infections  HIV treatment requires more resources than any other single area of the HIV and AIDS response  UNAIDS : 39% of all resources for HIV  Exciting time in the discussion on ART:  call from UNAIDS: 90% diagnosed, 90% on ART; 90% virally suppressed by 2020 Why focus on HIV Treatment?

 93 countries included in the analysis, based on criteria:  More than 1,000 PLHIV in country  Eligible for Global Fund funding for HIV in 2014  Countries grouped into the following 6 regions:  Africa: West and Central (AWC) - 22  Africa: East and Southern (AES) - 20  Latin America and the Caribbean (LAC) - 14  Middle East and North Africa (MENA) - 9  Eastern Europe and Central Asia (EECA) - 12  Asia and the Pacific (AP) - 16 Country Inclusion Criteria

Projecting Global HIV Treatment Needs

* Depending on current country guidelines as preset in Spectrum. # HIV & TB co-infected with CD4 above 350 (or 500) are a very small proportion; not included in this round of analysis.  Used AIM in Spectrum to estimate projected numbers of adult and pediatric patients that are eligible for ART from in each of the 93 countries.  Spectrum AIM was used individually for each country  Two eligibility scenarios:  Current eligibility # :  Adult: CD4<350 or 250* and Option B+ (all HIV+ PW)  Children: CD4<350 for ages 5-14; CD4<750 for ages mo.; all under 24 mo. (irrespective of CD4)  WHO 2013 eligibility # :  Adult: CD4<500 and Option B+ (all HIV+ PW)  Children: CD4<500 for ages 5-14; all under 5 (irrespective of CD4) a) ART Need: Methods

Global Need for ART: Adults Source: Dutta, Barker, Kallarakal (forthcoming, 2014)

Global Need for ART: Pediatric Source: Dutta, Barker, Kallarakal (forthcoming, 2014)

* Sources: WHO/PAHO 2013 (“ART in Spotlight: LAC”); WHO et al. TUA Progress Report 2013, etc.  Coverage: Number on ART on Dec. 31 st / Need for ART, Dec. 31 st  Step 1: Established 2013 baseline coverage % for adults and children in each of 93 countries, looking at:  Number on ART from 2013 UNGASS country reports; national reports & documents*, or value in Spectrum (in this order)  Divided this by current need for ART on Dec. 31 st in the country  Step 2: Set possible scale-up paths for countries from this base:  9.17 million on ART in 2012, a 19.8% increase on 2011*  Two scale-up scenarios:  Slow scale-up: 20% annual increase in coverage %  e.g., country’s coverage in 2014: 40%; coverage in 2015: 48%  Fast scale-up: 30% annual increase in coverage % b) ART Coverage: Methods

Source: Dutta, Barker, Kallarakal (forthcoming, 2014) 2013 ART Coverage %: Adult Bubble size shows Current ART Need in 2013

2013 ART Coverage %: Pediatric Bubble size shows Current ART Need in 2013 Source: Dutta, Barker, Kallarakal (forthcoming, 2014)

 Step 1: Established 2013 split of patients on 1 st vs. 2 nd line ART, adults and children separately (if poss.)  By country: UNGASS 2013 country reports, national data, global/regional reports. WHO regional average used for missing  Step 2: Define region-specific annual migration rate ranges: % of 1 st line moving to 2 nd line, per year  A region has countries classified into “high / med. / low.” This range differs by region. Overall range across regions: 0.5% to 3% p.a.  Country designated within region based on resistance*, LTFU, etc.  Step 3: Migration scenarios by country over :  Base migration: As set above: assumes historical rates continue; increased detection with VL cancelled by lower proximal factors for failure  Higher migration: Migration increases from base : Increased patient load stresses systems; higher detection with VL, etc. – greater switching  E.g.: Country with low migration moves to medium; medium moves to high c) 1 st & 2 nd line ART: methods * Stanford Drug Resistance Database

ScenarioIDScenario Definition C20ScaleBM1Number of patients on 1st line ART regiment based on: current ART guidelines; Scale up of ART coverage by 20%, current migration scheme to 2nd line treatment C30ScaleBM1Number of patients on 1st line ART regiment based on: current ART guidelines; Scale up of ART coverage by 30%, current migration scheme to 2nd line treatment C20ScaleHM1Number of patients on 1st line ART regiment based on: current ART guidelines; Scale up of ART coverage by 20%,higher migration scheme to 2nd line treatment C30ScaleHM1Number of patients on 1st line ART regiment based on: current ART guidelines; Scale up of ART coverage by 30%, higher migration scheme to 2nd line treatment WHO20ScaleBM1 Number of patients on 1st line ART regiment based on: WHO2013 ART guidelines; Scale up of ART coverage by 20%, current migration scheme to 2nd line treatment WHO30ScaleBM1 Number of patients on 1st line ART regiment based on: WHO ART guidelines; Scale up of ART coverage by 30%, current migration scheme to 2nd line treatment WHO20ScaleHM1 Number of patients on 1st line ART regiment based on: WHO 2013 ART guidelines; Scale up of ART coverage by 20%,higher migration scheme to 2nd line treatment WHO30ScaleHM1 Number of patients on 1st line ART regiment based on: WHO 2013 ART guidelines; Scale up of ART coverage by 30%, higher migration scheme to 2nd line treatment Median_1st_lineMedian of all 1st line scenario totals C20ScaleBM2Number of patients on 2nd line ART regiment based on: current ART guidelines; Scale up of ART coverage by 20%, current migration scheme to 2nd line treatment C30ScaleBM2Number of patients on 2nd line ART regiment based on: current ART guidelines; Scale up of ART coverage by 20%, current migration scheme to 2nd line treatment C20ScaleHM2Number of patients on 2nd line ART regiment based on: current ART guidelines; Scale up of ART coverage by 20%, high migration scheme to 2nd line treatment C30ScaleHM2Number of patients on 2nd line ART regiment based on: current ART guidelines; Scale up of ART coverage by 20%, high migration scheme to 2nd line treatment WHO20ScaleBM2 Number of patients on 2nd line ART regiment based on: WHO2013 ART guidelines; Scale up of ART coverage by 20%, current migration scheme to 2nd line treatment WHO30ScaleBM2 Number of patients on 2nd line ART regiment based on: WHO2013 ART guidelines; Scale up of ART coverage by 20%, current migration scheme to 2nd line treatment WHO20ScaleHM2 Number of patients on 2nd line ART regiment based on: WHO2013 ART guidelines; Scale up of ART coverage by 20%, high migration scheme to 2nd line treatment WHO30ScaleHM2 Number of patients on 2nd line ART regiment based on: WHO2013 ART guidelines; Scale up of ART coverage by 20%, high migration scheme to 2nd line treatment Median_2st_lineMedian of all 2nd line scenario totals

Projected number of Adults on 2 nd Line ART High: 3.9 million Low: 2.2 million Source: Dutta, Barker, Kallarakal (forthcoming, 2014) Range based on 8 scenarios

Projected number of Children on 2 nd Line ART High: 262 thousand Low: 143 thousand Source: Dutta, Barker, Kallarakal (forthcoming, 2014) Range based on 8 scenarios

Projected numbers on ART: Adult Based on increasing coverage from current base High : 29.2 million Low : 22.1 million Source: Dutta, Barker, Kallarakal (forthcoming, 2014) Range based on 16 scenarios

High: 2 million Low: 1.3 million Source: Dutta, Barker, Kallarakal (forthcoming, 2014) Range based on 16 scenarios Projected numbers on ART: Ped. Based on increasing coverage from current base

Cost of HIV Treatment

 Used regional average patient-year costs by income category for WHO-preferred regimens  Annual drug costs from WHO Global Price Reporting Mechanism database; as regional averages by income level  Most prices are from 2013 (transactions before 2011 excluded)  Assumed regimen prices stable from 2014 to 2020, in 2013 $  Substituted global averages, matching income level, for any missing region/income level and regimen data  Regimen splits and per year costs reviewed against country-specific costing studies from HPP (2014) and CHAI (2012) Costing Methods: Annual ARVs Adult 1 st lineAdult 2 nd linePediatric 1 st linePediatric 2 nd line TDF + 3TC + EFVZDV+3TC+LPV/rABC+3TC + LPV/rZDV + 3TC + EFV ZDV+3TC+NVPTDF+FTC+LPV/rZDV + 3TC + LPV/rABC + 3TC + EFV ZDV+3TC+EFVABC + 3TC + EFVZDV + 3TC + LPV/r ZDV+3TC+EFVABC + 3TC +LPV/r

 Lab costs: 3 scenarios x 3 income levels  Compiled estimates of country-specific unit costs* per test into averages by low, low-middle and middle income level groups  Three cost scenarios per income level: via # tests and unit cost:  Facility-level costs**  Average % of direct commodity costs (ARV and lab) that is spent on personnel and overhead (building utilities and contracted services)  Percentages differ by income level group  Assumed stable percentage of costs from Costing Methods: Lab and Facility-Level Costs Scenario → High costMedium costLow cost CD41 x yr., avg. unit cost2 x yr., avg. unit cost2 x yr., lowest unit cost Viral load Routine, avg. unit cost Targeted (5%), avg. unit cost Targeted (5%), lowest unit cost Hematology and clinical chemistry 2 x yr., avg. unit cost 2 x yr., lowest unit cost Sources: * HPP 2014, CHAI 2013, MSF 2013; many others; Sources: ** Gallaraga et. al 2011, PEPFAR 2013, many others

 Highest cost scenario  Highest numbers on treatment  WHO 2013 eligibility, 30% annual scale-up rate in coverage, highest 2 nd line migration scenario  Highest unit cost for lab  Medium cost scenario  Median numbers on treatment  Medium unit cost for lab  Lowest cost scenario  Lowest numbers on treatment  Current eligibility, 20% annual scale-up rate in coverage, current 2 nd line migration scenario  Lowest unit cost for lab Total costs: Three Scenarios

Total Annual ART Costs (93 countries): ARVs, lab, personnel, and facility-level costs High: $8.5 billion Low: $5.5 billion All costs in 2013 US$. Source: Dutta, Barker, Kallarakal (forthcoming, 2014)

Disaggregating total costs of ART for 93 countries: Medium Scenario All costs in 2013 US$. Source: Dutta, Barker, Kallarakal (forthcoming, 2014)

Proportion of Total Costs : Medium Scenario Source: Dutta, Barker, Kallarakal (forthcoming, 2014)

Sources: PEPFAR 2013 COPs (sum of budget codes HBHC, HKID, HLAB, HTXD, HTXS, HVTB, PDCS, PDTX only); GFATM 2014 disbursement report (July 2014 update)  Annual level of GFATM funding for HIV  Based on late 2013 and 2014 funding disbursements for all open HIV grants, excluding civil society organization PRs  Global total: $558.7 million/year  Annual level of PEPFAR funding for ART  2013 funding commitments for treatment and care for 31 countries  Total: $1.95 billion/year  3 funding gap scenarios:  Largest gap: Highest cost scenario, current GFATM funding stays constant, subtracted 30% from PEPFAR funding (overhead)  Medium gap: Median cost scenario, current PEPFAR and GFATM funding, constant over time  Smallest gap: Lowest cost scenario, current PEPFAR and GFATM funding, constant over time Funding gap analysis: Methods

Annual funding gap across 93 countries (prior to domestic contribution) Includes ARV, lab, personnel and overhead costs High: $6.6 billion Low: $2.9 billion All values in 2013 US$. Source: Dutta, Barker, Kallarakal (forthcoming, 2014)

High: $4.8 billion Low: $1.7 billion All values in 2013 US$. Source: Dutta, Barker, Kallarakal (forthcoming, 2014) Annual funding gap across 93 countries (prior to domestic contribution) Includes ARV and lab costs only

Emerging Themes: E 2 in HIV Treatment

 Need to increase cost-efficiency:  Continue to reduce ARV prices and wider use of low-cost WHO- recommended regimens  Example: A 5% reduction in ARV prices could save as much as $1.5 billion from  Reduce facility-level costs  Example: Reducing proportion of direct costs spent on personnel and overhead by 5% would save as much as $485 million from  Reduce lab costs  Example: Reducing unit costs of all lab tests to the lowest current price would save as much as $2.5 billion from  Need to increase effectiveness:  How to increase coverage by 20-30% per year on existing base?  Better use of viral load testing to detect and switch on failure  Prevent large rise in future 2 nd line treatment need Key Findings

Potential E 2 Gains across ART cascade Interventions that reduce ART costs Interventions that promote sustained viral suppression up to 90% Decentralize, but maintain viable facility- level patient loads Treatment simplification: new methods to deliver ARVs with lower pill burden; long-term dosing Task shifting: reduce per-patient personnel costs Better patient monitoring whether via virological or immunological testing Further expansion of FDC formulations Community-based models of patient monitoring and adherence support Consolidation of lower cost platforms for viral load testing, even at POC; reduction of reagent costs Treat comorbidities, including malnutrition, to keep patient healthy and in care Critical short-term investments (e.g., new VL equipment) may lead to long-term efficiency and effectiveness gains Interventions that help increase coverage up to 90% or more Reduce cross-cutting delivery challenges Eliminate losses across ART cascade (75% lost from test to treat? Mugglin et al. 2012) Treatment site positioning and strengthening; timing; family-based approaches, structural/social enablers.

 Assessment of needs  Serodiscordant couples (also recommended) not included  Coverage projections  Not able to use UNAIDS/WHO 2014 Country Progress Reports, data not released  Costs of ART missing  Costs of OI treatment (non-TB), psychosocial support, nutrition, where these are available  Above-facility level costs (programmatic support, training)  Gap analysis issues  Overestimation of both GFATM and PEPFAR funds - values are not specific to cost categories included. Data not available Limitations of analysis

HPP Studies on E 2

Lessons Learned from Kenya Efficient interventionsEffective interventions HIV testing; MoH switched testing algorithm to yield highest cost savings while maintaining accuracy Option B+; averts more infant and adult infections than Option B, but at a significant additional cost HCW training; harmonized in-service training curriculum with long-term mentoring is cost- efficient Harm reduction services for key populations; combination package (NSP, MAT, HCT, and ART for PWID) is cost-effective (ICER of $1,600) Screening blood supply for transfusions; cost- benefit ratio of 3 for additional costs to screen all blood vs. averted TTI treatment costs Oral PrEP for sex workers; cost-effectiveness ratio in Kenya is $25 per HIV infection averted; costs could decrease through task shifting New ART guidelines; adopting WHO 2013 guidelines would result in a significant reductions in new HIV infections and premature deaths Workplace interventions; mainstream HIV response, promote prevention programs, fight stigma and discrimination

Lessons Learned from Mozambique  Need to increase allocative efficiency:  Target geographic regions and population groups contributing the most to HIV incidence  Need to scale-up biomedical and behavior change interventions to achieve greatest health impact  Revised HIV acceleration plan could avert 113,927 new infections and 145,668 AIDS-related deaths  Need both types of interventions to reach goal of halving HIV incidence by 2017

Thank You! The Health Policy Project is a five-year cooperative agreement funded by the U.S. Agency for International Development under Agreement No. AID-OAA-A , beginning September 30, The project’s HIV activities are supported by the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR). It is implemented by Futures Group, in collaboration with Plan International USA, Futures Institute, Partners in Population and Development, Africa Regional Office (PPD ARO), Population Reference Bureau (PRB), RTI International, and the White Ribbon Alliance for Safe Motherhood (WRA).