1. Return on investment: How do whole societies benefit from improved services and coverage for key populations? Bradley Mathers Kirby Institute • UNSW Australia

2. Return on investment

3. What are the potential returns? COMPREHENSIVE PACKAGE OF INTERVENTIONS CRITICAL ENABLERS HEALTH SECTOR INTERVENTIONS ▼Stigma and discrimination HIV prevented ▲Social inclusion + participation ▼HIV related mortality ▼HIV related morbidity HIV managed ▲Welfare + safety Other conditions prevented ▼ related mortality ▼ related morbidity Other conditions managed ▲Confidence + positive living ▼ Health expenditure ($) ▲ Productivity ($) ▲ Happiness ▲ Wellbeing

4. Benefit to key populations and to society as a whole

5. Prevalence of men who have sex with men1, people who inject drugs2 and female sex workers3 Eastern Europe MSM: 3.0 - 27.0% PWID:0.8 – 2.1% FSW: 0.4 – 1.5% Western Europe MSM:– PWID: 0.2 – 0.4% FSW: 0.1 - 1.4% North America MSM:– PWID: 0.6 – 0.8% FSW: – Central Asia MSM:– PWID: 0.7 – 0.9% FSW: 0.1 - 0.8% East and South Asia MSM: 0.01 - 58.8% PWID: 0.1 – 0.2% FSW: 0.3 – 2.6% Middle East & N Africa MSM:– PWID: 0.05 - 0.1% FSW:– Latin America & The Caribbean MSM: 1.0 - 48.5% PWID: 0.2 – 0.5% FSW: 0.2 - 7.4% Sub Saharan Africa MSM:1.0 – 60.0% PWID: 0.1 – 1.1% FSW: 0.4 - 4.3% Oceania MSM:2.5 – 5.7% PWID: 0.5 – 0.6% FSW:– 1. Caceres et al. (2008) Epidemiology of male same-sex behaviour and associated sexual health indicators in low- and middle-income countries. 2. UNODC (2014) World Drug Report. 3. Vandepitteet al. (2006) Estimates of the number of female sex workers in different regions of the world

6. Distribution of new HIV infections across risk groups Estimated using UNAIDS Mode of Transmission model; * uses Asian Epidemiological Model (AEM)

7. Distribution of new HIV infections across risk groups Estimated using UNAIDS Mode of Transmission model; * uses Asian Epidemiological Model (AEM)

8. Distribution of new HIV infections across risk groups Estimated using UNAIDS Mode of Transmission model; * uses Asian Epidemiological Model (AEM)

9. Allocative efficiency What is the impact of investing in strategies for key populations?

10. The Optima Model • Mathematical model of HIV transmission and disease progression • Integrated with costing and financial analysis framework • Provides outputs on how best to allocate available resources for a range of outcomes including how to: • Minimize incident HIV infections • Save disability adjusted life years (DALYs) • Minimize spending commitments • Meet other defined targets http://optimamodel.com/index.html DP Wilson, R Gray, C Kerr, A Shattock, R Stuart. The Kirby Institute.

11. Allocative efficiency example #1: An African country with a low level HIV epidemic

12. Allocative efficiency example #1: An African country with a low level epidemic • HIV prevalence - General population: 0.54% • - Female sex workers: 1.60 – 10.0% • - Men who have sex with men: 1.9 – 6.3% • Estimated 6,400 new infections in 2013 (Gen. poplnincidence 0.05%) Projected incidence if 2013 spending levels remain constant 2013 New infections per year (1000s) • Low income country • HIV response largely reliant on donor funding (over 65% in 2013) • Decreasing amount of funding available • Budget of USD 6.4 million available for HIV response in 2013 Personal communication:R Stuart, A Shattock, R Gray& DP Wilson, The Kirby Institute in collaborationwith the World Bank (2014)

13. Actual 2013 budget allocation ‘Optimised’ budget allocation Generalpopulation HTC Gen.pop. condom pgm. 19,000 infections averted Lower risk males Cumulative incidence 2013 - 2020 Lower risk males Personal communication:R Stuart, A Shattock, R Gray& DP Wilson, The Kirby Institute in collaborationwith the World Bank (2014)

14. Allocative efficiency example #2: A concentrated epidemic in an Eastern European country

15. Allocative efficiency example #2:Belarus – concentrated epidemic • Upper-middle-income economy • HIV response reliant on international donor funding (~50% in 2011) • HIV prevalence - General population: 0.2%(2008)  0.4%(2012) • - People who inject drugs: 15% • - Female sex workers: 5.8% • - Men who have sex with men: 4.0% • Incidence is increasing • Primary mode of infection shifting from injecting to sexual transmission Projected incidence New infections per year (1000s) DP Wilson et al. HIV resource needs, efficient allocation and resource mobilization for the Republic of Belarus. Report for UNAIDS, 2013

16. Current budget allocation ‘Optimised’ budget allocation New infections per year (1000s) DP Wilson et al. HIV resource needs, efficient allocation and resource mobilization for the Republic of Belarus. Report for UNAIDS, 2013

17. In summary • Key populations disproportionally affected • Proven effective strategies exist • Substantial health, social and economic benefits to be gained both by people from key populations and society as a whole • Limited resources are potentially wasted by not investing in key populations

18. bmathers@kirby.unsw.edu.au