1. IAEN Conference (20 July 2018)
The impact of differential uptake by HIV risk group on the effect and cost-effectiveness of PrEP in different populations in South Africa
 Lise Jamieson1, Gesine Meyer-Rath1,2, Gabriela Gomez3,4,
Leigh F. Johnson5
1 Health Economics and Epidemiology Research Office (HE2RO), University of the Witwatersrand, South Africa 2 Department of Global Health, Boston University, Boston, USA 3 Department of Global Health and Development, Faculty of Public Health and Policy, LSHTM, UK 4 Wits Reproductive Health and HIV Institute, University of Witwatersrand, South Africa 5 Centre for Infectious Disease Epidemiology and Research, University of Cape Town, South Africa
IAEN Conference (20 July 2018)

2. Objectives
What is the cost and epidemiological impact of providing PrEP to different target populations in South Africa?
What would be the most cost-effective population to target?
Would this change if people self-selected based on increased risk?

3. Process
Worked alongside the DoH’s PrEP technical working group while developing the PrEP guidelines for South Africa
Regularly updated cost and effectiveness data based on experiences in ongoing demonstration projects
Results informed priority setting and budgets for roll- out (though not targets)
Ongoing discussion about between “PrEP only” and integration of other (STI/prevention) services into PrEP

4. Modelling methods
The epidemiological impact was ascertained using the Thembisa model, a compartmental HIV transmission model fitted to the South African HIV epidemic
PrEP was scaled-up linearly over 3 years from 2019 to target coverage of
18% for young adults and adolescents, pregnant women
70% for MSM
95% for FSW
Sub-scenarios in which only the high risk sub-population would select to initiate PrEP, emulating self-selection of those who deem themselves at high risk of HIV acquisition
PrEP effectiveness: 65% (85% in MSM), time on PrEP: 2 years
Evaluated the impact of PrEP on the entire HIV programme over 20 years ( )
Thembisa – Leigh Johnson, UCT
65% effectiveness – Fonner et al placed effectiveness between 46-66%, but this is likely to be an underestimate as they came from randomized trials prior to PrEP being established as effective.
High risk group – individuals who have a propensity to engage in concurrent sexual partnerships and/or commercial sex (25% of women, 35% of men, based on studies that have estimated this)
Low risk group – individuals who are serially monogamous.

5. PrEP unit cost Provider perspective
Ingredients-based costing, based on PrEP guidelines
Assumes generic drugs, lower staff cadre, includes demand creation and targeting costs
Resource use data based on PrEP demonstration projects to female sex workers (FSW) [Project TAPS, Wits RHI], men who have sex with men (MSM) [ANOVA], adolescent girls and young women [ACCESS]
Separate unit cost for young adults (20-24 yrs), adolescents (15-19 yrs) of both genders, pregnant women, FSW and MSM

6. PrEP unit cost (2017 USD) per person per year
Young women
(20-24)
Female
adolescents
(15-19)
Pregnant women
FSW
Young
men
Male adolescents
MSM
First year
$160
$100
$162
$159
$158
Follow-up
$140
$139
$138
PrEP cost per person per year is $ (non- pregnant), $100 (pregnant)
Average cost of ART = $286 per person per year
PrEP costs (non-preg) around $160 for the first year and $140 for follow-up years, the price differential being due to increased monitoring costs in the first year. Pregnant women $100 for duration of pregnancy, thereafter same as young women
The cost per person is around half the cost of ART

7. PrEP unit cost: Cost drivers
Our staff costs are embedded within these cost categories, and make up ~23% of the total PrEP unit cost

8. Impact of PrEP on HIV incidence
Virtual elimination (incidence < 0.1%)
Before we talk about the impact of PrEP on HIV incidence we should talk about HIV incidence historically. We are already over the hump of it and HIV incidence has been on the decline. It is in this context that we are looking at the impact of PrEP

9. Impact of PrEP on new HIV infections

10. Impact of PrEP on new HIV infections averted

11. Impact of PrEP on new HIV infections averted

12. Impact of PrEP on incremental cost of HIV programme (2017 USD)

13. Impact of PrEP on incremental cost of HIV programme (2017 USD)

14. PrEP cost effectiveness (2019-38)
Young women
(20-24)
Female adolescents
(15-19)
Pregnant women
FSW
Young men
Male adolescents
MSM
Risk group
All HR
Coverage
18%
95%
70%
No. of person years on PrEP [millions]
9.8
1.9
7.3
2.0
6.3
2.4
10.2
4.0
5.8
2.6
4.4
New HIV infections averted [thousands]
(% change)
110 (2.9%)
88 (2.3%)
159 (4.3%)
140 (3.7%)
76 (2.0%)
162 (4.4%)
139 (3.7%)
130 (3.4%)
99 (2.6%)
94 (2.4%)
199 (5.5%)
Incremental cost [millions 2017 USD]
1,186 (2.7%)
122 (0.3%)
749 (1.7%)
45 (0.1%)
843 (1.9%)
75 (0.2%)
1,218 (2.8%)
377 (0.9%)
666 (1.5%)
232 (0.5%)
345 (0.8%)
ICER [2017 USD/HIV infection averted]
10,776
1,386
4,718
319
11,062
464
8,781
2,894
6,755
2,469
1,730

15. PrEP cost effectiveness (2019-38)
Young women
(20-24)
Female adolescents
(15-19)
Pregnant women
FSW
Young men
Male adolescents
MSM
Risk group
All HR
Coverage
18%
95%
70%
No. of person years on PrEP [millions]
9.8
1.9
7.3
2.0
6.3
2.4
10.2
4.0
5.8
2.6
4.4
New HIV infections averted [thousands]
(% change)
110 (2.9%)
88 (2.3%)
159 (4.3%)
140 (3.7%)
76 (2.0%)
162 (4.4%)
139 (3.7%)
130 (3.4%)
99 (2.6%)
94 (2.4%)
199 (5.5%)
Incremental cost [millions 2017 USD]
1,186 (2.7%)
122 (0.3%)
749 (1.7%)
45 (0.1%)
843 (1.9%)
75 (0.2%)
1,218 (2.8%)
377 (0.9%)
666 (1.5%)
232 (0.5%)
345 (0.8%)
ICER [2017 USD/HIV infection averted]
10,776
1,386
4,718
319
11,062
464
8,781
2,894
6,755
2,469
1,730

16. PrEP cost effectiveness (2019-38)
Young women
(20-24)
Female adolescents
(15-19)
Pregnant women
FSW
Young men
Male adolescents
MSM
Risk group
All HR
Coverage
18%
95%
70%
No. of person years on PrEP [millions]
9.8
1.9
7.3
2.0
6.3
2.4
10.2
4.0
5.8
2.6
4.4
New HIV infections averted [thousands]
(% change)
110 (2.9%)
88 (2.3%)
159 (4.3%)
140 (3.7%)
76 (2.0%)
162 (4.4%)
139 (3.7%)
130 (3.4%)
99 (2.6%)
94 (2.4%)
199 (5.5%)
Incremental cost [millions 2017 USD]
1,186 (2.7%)
122 (0.3%)
749 (1.7%)
45 (0.1%)
843 (1.9%)
75 (0.2%)
1,218 (2.8%)
377 (0.9%)
666 (1.5%)
232 (0.5%)
345 (0.8%)
ICER [2017 USD/HIV infection averted]
10,776
1,386
4,718
319
11,062
464
8,781
2,894
6,755
2,469
1,730

17. PrEP cost effectiveness (2019-38)
PrEP intervention
ICER
(USD/HIV averted)
Female adolescents (15-19), HR
319
FSW
464
Young women (20-24), HR
1,386
MSM
1,730
Male adolescents (15-19), HR
2,469
Young men (20-24), HR
2,894
Female adolescents (15-19), all
4,718
Male adolescents (15-19), all
6,755
Young men (20-24), all
8,781
Young women (20-24), all
10,776
Pregnant women
11,062
Here is an ICER table, depicting cost per HIV infection averted, ranked by the PrEP interventions targeted to the individual population groups.

18. Uncertainties Modelling: Cost:
Successful selection of high risk sub-population
Effectiveness modelled: 65% (85% MSM)
Time on PrEP: 2 years
Coverage (targets/ demand)
PrEP cycling
Cost:
Integration of other services (STI, prevention) into PrEP
Very hard to target PrEP to just the high risk group – people are often not good at assessing their own risk and risk scoring algorithms generally perform poorly in predicting who gets infected.
Uptake – demonstration sites – 5% (uni), 13% (SW), MSM (54%)

19. Uncertainty: PrEP coverage impact on HIV (2019-38)

20. Uncertainty: PrEP coverage impact on cost (2019-38)

21. Conclusion
PrEP averts between 2.0% and 5.5% of new HIV infections in the next 20 years overall impact of PrEP on the HIV epidemic is relatively small, regardless of target population and self-selection by risk
PrEP increases cost of the HIV programme by 0.1% to 2.8% in the next 20 years
Successful targeting of high risk groups can render it more cost effective or even cost-saving in the longer terms
Most cost-effective is PrEP provision to high-risk female adolescents, then FSW, then high-risk young women, then MSM, then high-risk young men and adolescents, then all others. PrEP provision to pregnant women is the least cost effective option.