John M Blandford, PhDChief – Health Economics, Systems and Integration Branch

Division of Global HIV/AIDSU.S. Centers for Disease Control and Prevention

Nairobi, Kenya14 October 2011

Estimating Health Impact and Costs of Treatment in PEPFAR-

Supported Programs

Center for Global HealthDivision of Global HIV/AIDS

2

Evolving Use of Cost Data under PEPFAREarly emphasis on robust cost analyses and projections• Support planning and

efficient implementation• Focus on total and USG

costs for each patient-year of treatment

Need to account more fully for societal impact of treatment • Direct benefits to patient• Indirect benefits to

society• Averted costs Note: Per-patient budget allocation is estimated as treatment allocation

divided by lagged end-of-reporting direct patients.

2004 2005 2006 2007 2008 2009$0

$200

$400

$600

$800

$1,000

$1,200

0

500000

1000000

1500000

2000000

2500000

3000000

PEPFAR Per-Patient ART Cost No. of Direct ART Patients

Scale-Up of ART Access and Declining PEPFAR Per-Patient Costs, 2004-2009

3

Modeling the Impact and Costs of Treatment in PEPFAR-Supported

ProgramsTwo complementary analytic approaches:1. Estimation of health impact and net

societal cost of PEPFAR-supported treatment

2. Estimation of longer-term epidemic impact and costs of accelerated scale-up in light of HPTN 052

4

ESTIMATING HEALTH IMPACT AND SOCIETAL COST OF TREATMENT UNDER PEPFAR

Modeling the Impact and Costs of Treatment

5

PEPFAR ART Cost Model (PACM) Background

Developed to estimate resource requirements for treatment scale-up Designed to inform USG planning at

global and country levels Utilizes data from multi-country

PEPFAR ART Costing Project Study, other PEPFAR-supported studies

Open-cohort state-transition model Model projects estimates of patient

populations by patient type Size of patient population, by patient

type, recalculated on a quarterly basis

Direct treatment costs are estimated for each patient group

Model structure and assumptions reviewed by Government Accountability Office (GAO)

Summary Results for ART Patients: PEPFAR Global HIV Treatment Cost Projection Model

Projection Period, Countries, and Funding to Include Links: PRE-ART SUMMARY

DETAILED COST RESULTS

DETAILED PT RESULTS

SENS ANALYSIS PARAMETERS

SENS ANALYSISART

SENS ANALYSISPRE-ART

RAW COST DATA

Start Year (e.g. 2009): 2010

Costs Included: TRUE FALSE

TRUE TRUE

Total Annual Costs Over 10 Years

Time Period

Non-ARV Recurrent

Costs

Non-ARV Investment

CostsAntiretroviral

Drugs

Country-level Admin and

Support

Country Indirect Support

TOTAL ART COSTS

FY2010 451.1$M 63.9$M 456.0$M 257.5$M 150.0$M 1,378.6$M

FY2011 547.7$M 65.4$M 587.4$M 306.6$M 250.0$M 1,757.1$M

FY2012 628.4$M 65.6$M 698.5$M 329.6$M 300.0$M 2,022.1$M

FY2013 693.7$M 64.5$M 776.4$M 341.2$M 350.0$M 2,225.8$M

FY2014 742.1$M 62.0$M 847.5$M 341.7$M 400.0$M 2,393.3$M

FY2015 779.3$M 61.6$M 890.0$M 336.4$M 450.0$M 2,517.3$M

FY2016 815.6$M 64.3$M 914.8$M 352.0$M 450.0$M 2,596.7$M

FY2017 853.7$M 67.2$M 938.0$M 368.4$M 450.0$M 2,677.3$M

FY2018 893.1$M 70.1$M 956.1$M 385.3$M 450.0$M 2,754.6$M

FY2019 933.8$M 73.1$M 974.6$M 402.8$M 450.0$M 2,834.2$M

10-Year Total: 7,338.5$M 657.7$M 8,039.3$M 3,421.3$M 3,700.0$M 23,156.8$M

Total Patient Volume at End of Each Year

Time PeriodAdult

PatientsPediatric Patients

1st-Line Regimens

2nd-Line Regimens

ALL ARTPATIENTS

Start 2,286,493 198,825 2,361,052 124,266 2,485,318

End Of FY2010 2,856,840 288,478 2,940,240 205,078 3,145,318

End Of FY2011 3,322,837 362,481 3,383,982 301,336 3,685,318

End Of FY2012 3,684,169 421,149 3,697,909 407,409 4,105,318

End Of FY2013 3,940,826 464,492 3,887,864 517,454 4,405,318

End Of FY2014 4,092,799 492,519 3,958,995 626,323 4,585,318

End Of FY2015 4,192,579 512,739 3,975,596 729,722 4,705,318

End Of FY2016 4,292,654 532,664 3,999,477 825,841 4,825,318

End Of FY2017 4,393,012 552,306 4,030,135 915,183 4,945,318

End Of FY2018 4,493,643 571,675 4,066,762 998,556 5,065,318

End Of FY2019 4,594,533 590,785 4,108,648 1,076,670 5,185,318

Annual Per-Patient Costs for Different Patient Groups* Annual Per-Patient Cost, Disaggregated by Cost Category*

Time PeriodAdult

PatientsPediatric Patients

1st-Line Patients

2nd-Line Patients

ALL ART PATIENTS Time Period

Non-ARV Recurrent

Costs

Non-ARV Investment

CostsAntiretroviral

Drugs

Country-level Admin and

SupportALL ART

PATIENTS

FY2010 431$ 489$ 405$ 942$ 436$ FY2010 160$ 23$ 162$ 91$ 436$

FY2011 438$ 474$ 406$ 887$ 441$ FY2011 160$ 19$ 172$ 90$ 441$

FY2012 440$ 462$ 401$ 856$ 442$ FY2012 161$ 17$ 179$ 85$ 442$

FY2013 438$ 465$ 394$ 828$ 441$ FY2013 163$ 15$ 182$ 80$ 441$

FY2014 441$ 465$ 391$ 800$ 443$ FY2014 165$ 14$ 189$ 76$ 443$

FY2015 443$ 461$ 388$ 776$ 445$ FY2015 168$ 13$ 192$ 72$ 445$

FY2016 449$ 466$ 390$ 760$ 450$ FY2016 171$ 13$ 192$ 74$ 450$

FY2017 454$ 469$ 393$ 745$ 456$ FY2017 175$ 14$ 192$ 75$ 456$

FY2018 459$ 471$ 396$ 731$ 460$ FY2018 178$ 14$ 191$ 77$ 460$

FY2019 464$ 474$ 401$ 718$ 465$ FY2019 182$ 14$ 190$ 79$ 465$

10-Year Average: 447$ 469$ 396$ 773$ 449$ 10-Yr Average: 169$ 15$ 186$ 79$ 449$ *Excludes Country Indirect Support*Excludes Country Indirect Support

INPUTS:ARV REGIMENS

OTHER DATAINPUTS: PARAMETERS

INPUTS:ARV PRICES

INPUTS: NON-ARV COSTS

STATE TRANS. MODEL

$M-

$M500.0

$M1,000.0

$M1,500.0

$M2,000.0

$M2,500.0

$M3,000.0

FY2010 FY2011 FY2012 FY2013 FY2014 FY2015

Total Annual Treatment Cost, by Fiscal Year

Country Indirect Support

Country-level Admin and SupportAntiretroviral Drugs

0500,000

1,000,0001,500,0002,000,0002,500,0003,000,0003,500,0004,000,0004,500,0005,000,000

Start FY2010 FY2011 FY2012 FY2013 FY2014 FY2015

Tota

l Dire

ct P

atien

ts

Year

Total Direct Patients at End of Year

Pediatric Patients

Adult Patients

$-

$100

$200

$300

$400

$500

$600

$700

$800

$900

$1,000

FY2010 FY2011 FY2012 FY2013 FY2014 FY2015 FY2016 FY2017 FY2018 FY2019

Adult Patients Pediatric Patients 1st-Line Patients 2nd-Line Patients

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

Start FY2010 FY2011 FY2012 FY2013 FY2014 FY2015 FY2016 FY2017 FY2018 FY2019

2nd-Line Regimens 1st-Line Regimens

$-

$50

$100

$150

$200

$250

FY2010

NonAntiretroviral Drugs

LOCAL GOVT AND OTHER DONORSPEPFAR FUNDING

LOW-INCOME COUNTRIES MIDDLE-INCOME COUNTRIES

6

Estimation of Health Impact and Net Societal Cost of PEPFAR-Supported

Treatment Patient population and cost estimates are

inputs for model of health impact and societal cost Estimates the broad health of PEPFAR-supported

treatment programs for patients and others who are impacted

Estimates societal cost of treatment, considering costs that are averted through effective treatment

Counterfactual: no program or program of different scale

7

Estimation of Health Impact and Net Societal Cost of PEPFAR-Supported

TreatmentEstimation of health impact from treatment Direct benefit (to treatment patients)

HIV-attributable deaths averted Life-years saved

Indirect benefit (to others) Averted secondary infections

• Sexual• Vertical: women who become pregnant while on ART

Averted orphanhood Life-years saved

Notes: A discount rate of 3% is used for calculation of future benefits and costs . Life-years saved do not currently account for quality or disability adjustments.

8

Estimation of Health Impact and Net Societal Cost of PEPFAR-Supported

TreatmentEstimation of net societal costs Net costs = treatment costs – averted costs

Treatment costs• Total program costs• All sources of support (e.g., PEPFAR, GFATM, national)

Averted costs• Medical costs for HIV-related illness• ART for secondary infections• Orphan care • Note: Averted productivity losses are not currently

estimated in the model

Note: A discount rate of 3% is used for calculation of future benefits and costs . Life-years saved do not currently account for quality or disability adjustments.

9

Key Preliminary Findings of PACM Estimates

1. For every one patient-year of HIV treatment provided, 2.2 discounted life-years are gained for society

2. For every 1000 patient-years of PEPFAR-supported HIV treatment provided: 228 HIV patients avert death 449 children avert orphanhood 61 sexual transmissions are averted 26 vertical (mother-to-child) transmissions are averted

10

Key Preliminary Findings of PACM Estimates

3. Cost savings to society that result from averted negative outcomes equal 59% of total treatment program costs

4. The net societal cost of treatment is $147 per discounted life-year gained when the indirect benefits and averted costs from treatment are considered Based on WHO standards for cost-effectiveness, ART

may potentially be highly cost-effective in most of sub-Saharan Africa

1 year

5 years

10 years

Infections Averted per 1,000 Patient-Years of Treatment

Source: Tim Hallett, Imperial College; The Impact of Treatment on HIV Incidence: Perspective from Epidemiology & Modelling

12

Current Limitations of PACM Estimates Input parameter for secondary sexual transmissions that

occur from non-acute PLWHA not on treatment requires further validation Base-case: Rate of 0.070 implies $147 per life-year saved CI: Rate of 0.560 – 0.930 implies $172 - $110 per life-year saved

Model does not capture dynamic effects of increased treatment coverage reducing community infectiousness Inclusion would likely improve estimated cost-effectiveness

No quality or disability adjustments currently estimated for life-years saved Inclusion would worsen estimated cost-effectiveness

Productivity gains from averted mortality and morbidity not currently estimated Inclusion would improve estimated cost-effectiveness

13

PRELIMINARY PROJECTIONS: EPIDEMIC IMPACT AND COST OF ACCELERATED SCALE-UP

Modeling the Impact and Costs of Treatment

14

Modeling the Impact and Costs of Treatment in PEPFAR-Supported

ProgramsTwo complementary analytic approaches:1. Estimation of health impact and net

societal cost of PEPFAR-supported treatment

2. Estimation of longer-term epidemic impact and costs of accelerated scale-up in light of HPTN 052

15

Modeled Example: Accelerated Treatment Scale-Up in Kenya

Desire to understand the potential epidemic impact and resource implications of accelerated treatment scale-up, in light of HPTN 052 findings What might be done in light of global health resource constraints? Understand the magnitude of economies required to allow

accelerated scale-up Collaboration with John Stover (Futures Institute)

Model based on AIDS Impact Model (AIM)/Spectrum to estimate epidemic impact and cost

Cost parameters derived from CDC’s PEPFAR ART Cost Model Kenya chosen as an example setting

16

Modeled Scenario: Rapid expansion of ART to patients already identified as

HIV-infected Priority groups for accelerated access in scenario:1. Patients with CD4 <500 cells/µl already on

waiting lists for ART or in pre-ART care 2. Lifelong ART to pregnant and breastfeeding

women regardless of CD4 cell count3. Patients with active tuberculosis (TB)4. Persons known to be in serodiscordant

couples regardless of CD4 count

17

Modeled Scenario: Rapid expansion of ART to patients already identified as

HIV-infected Efficiency gains: Utilizing a public health approach to treatment, it is assumed that costs might be further reduced

Standardized package of care and treatment Increased task-shifting Decentralization of care Streamlined commodity procurement and management

For Kenya example Treatment cost decline is modeled to decrease from $668 to

$491, over 5 years (26.5% decrease compared to current) Base case: Maintenance of 2011 coverage, no efficiency

gains

18

Base-Case for Kenya Projects 70% Coverage of Those Eligible for

Treatment (CD4<350)

Based on PEFPAR 2011 APR data

2010 2011 2012 2013 2014 20150%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

ART Coverage

<350 All HIV+

19

To Maintain Base Treatment Coverage, Continued Increase in Treatment

Required

2010 2011 2012 2013 2014 20150

100,000

200,000

300,000

400,000

500,000

600,000

700,000

20

Treatment Resources Would Need to Increase to Maintain Base Coverage

Levels

2011 2012 2013 2014 2015$0

$100,000,000

$200,000,000

$300,000,000

$400,000,000

$500,000,000

$600,000,000

TestingPMTCTPre-ARTART

21

With Accelerated Scale-Up an Additional 323,000 are Moved to Treatment

from Current Clinical Care and PMTCT

Based on population estimates in the following priority populations: patients in care with CD4<500, PMTCT patients, HIV patients with active TB, known PLHA in sero-discordant couples

2010 2011 2012 2013 2014 2015 -

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

900,000

1,000,000

Base Case Accelerated Scale-Up

22

Accelerated Scale-Up Results in Annual Decline in New HIV Infections

Under the base-case scenario, incident HIV infections remain relatively constant at or above 120,000 new cases per year. With accelerated treatment scale-up, incident HIV infections could be driven down to ~86,500 by 2015.

2010 2011 2012 2013 2014 20150

20,000

40,000

60,000

80,000

100,000

120,000

140,000

Accelerated Scale-upBase Case

23

Per Patient ART Costs ($/patient), under Base Case and Efficiency

Assumptions

2011 2012 2013 2014 2015$0

$100

$200

$300

$400

$500

$600

$700

$800

Base CaseEfficiency Scenario

24

Under Accelerated Scenario Annual Treatment Costs Reach Steady State

Over Time

Estimated costs to maintain current coverage levels in the Base Case and Accelerated Scale-Up Scenario. Flattened treatment costs in the accelerated scale-up scenario reflect effects of declining HIV incidence and additional implementation efficiency.

2011 2012 2013 2014 2015 2016 2017 2018 2019 2020$0

$100

$200

$300

$400

$500

$600

$700

$800

Accelerated Scale-UpBase Case

Mill

ions

25

Preliminary Findings from Accelerated Treatment Projections for Kenya

Accelerated scale-up could reduce incident infections by 31% over five years A flattened program results in steady incidence and a

growing population of those in need of treatment With reasonable assumptions for continued efficiency

gains, accelerated scale-up possible within constrained budget

In the longer term, accelerated scale-up may be cost-saving

Over five years in the context of the Kenyan epidemic, 93 infections are projected to be averted for every additional 1000 patient-years of treatment provided

For more information please contact:

John Blandford; Chief, Health Economics, Systems and Integration Branch; CGH/DGHATelephone: (404) 639-8070 E-mail: jblandford@cdc.gov

Nalinee Sangrujee; Lead, Health Economics and Finance Team; CGH/DGHA/HESIBTelephone: (404) 639-0942 E-mail: nsangrujee@cdc.gov

AcknowledgmentsJohn Stover – Futures InstituteNalinee Sangrujee – CDC-AtlantaNick Menzies – Harvard, CDC-AtlantaJ. Michel Tcheunche – CDC-AtlantaVimalanand Prabhu – CDC-AtlantaKipruto Chesang – CDC-KenyaLucy Nganga – CDC-Kenya Andrea Kim – CDC-KenyaNancy Knight – CDC-KenyaJan Moore – CDC-AtlantaLaura Broyles – CDC-Atlanta

Center for Global HealthDivision of Global HIV/AIDS