1. DEA expression for technical efficiency (TE) 1 Max for j=1, …, n, u r, v i ≥ 0 for all i and r Subject to

2. DEA framework with one input and one output 2 Total spending on ART Number of treated patients d1d1 d2d2 d3d3 d4d4 A B C D E F A, B, C, D, and E are efficient decision making units on the production frontier F is inefficient and below the frontier Efficiency score for input- oriented model equals to d 1 /d 2 Efficiency score for output- oriented model equals to d 3 /d 4

3. Means of inputs by year 3 YearObs. Spending (Million, $) Spending (Million, 2007 I$) Before 20044148.6128.2 Year 20053476.2182.3 Year 20064585.8187.6 Year 20073186.5167.0 Total15173.7166.0 Mean HIV/AIDS spending by year Obs denotes number of observations

4. Means of outputs by year 4 YearObs. Unweighted coverageWeighted coverage ARVVCTPMTCTARVVCTPMTCT Before 20044117.99%2.87%18.15%7.83%0.92%9.60% Year 20053423.02%5.02%27.15%16.76%1.02%18.70% Year 20064632.73%9.67%30.31%26.47%3.62%29.76% Year 20073139.16%19.19%38.77%34.79%10.96%44.30% Total15127.86%8.73%28.03%21.58%2.62%23.95% Mean coverage of VCT, PMTCT and ARV treatment

5. DEA models by year Average efficiency: 49.75% 5

6. Performance for 45 countries in 2006 6 Note: One output unit is one patient on ARV or equivalent for one year

7. Unit cost of national programs by output 7

8. Cautions with interpretation Unconditional efficiency scores may not perfectly match experts’ perception DEA does not account for measurement errors For countries that achieved 100% efficiency, the result does not mean that their efficiency cannot be improved in the future 8

9. Pooled DEA model by year 9

10. Component II: Determinants of efficiency of national HIV/AIDS programs Objective: –To indentify social and economic determinants of efficient HIV/AIDS programs Methods: Random-effects Tobit model –Model: –Dependent variable: log of efficiency –Independent variables Governance Political support Financing mechanism Economic and demographic characteristics –t denotes time and i denotes country 10

11. Regression on log efficiency (Random-effects Tobit model) 11 Independent variablesCoefficientP value Voice and accountability**0.3920.009 Government effectiveness0.5000.157 Rule of law-0.3330.333 Control of corruption-0.3230.297 Interaction of rule of law and control of corruption**0.6020.008 External source as percentage of total health expenditure **0.0300.004 Government source as percentage of total health expenditure*-0.0140.023 Government commitment to health*0.0310.042 Interaction of control of corruption and external share of health spending*0.0220.013 Log (GNI per capita)*3.4850.016 Square of log(GNI per capita)*-0.2070.026 Log (adult population)*0.1470.026 HIV/AIDS prevalence**0.0520.000 constant-20.4970.000

12. Conclusions 1 Substantial scope for improving HIV/AIDS programs –Output-oriented DEA: If countries performed optimally, given the resources available, outputs would double –Input-oriented DEA: If countries performed optimally, they would require half of the previous resources to achieve the previous level of services 12

13. Conclusions 2 Dollars matter, so does the efficiency of using dollars 13

14. Service scale- up mechanism Type of HIV/AIDS epidemic Low or concentrated (25 countries)Generalized (20 countries) Resource oriented (22 countries) Brazil, China, Jamaica, Mali, Mauritius, Paraguay, Peru, Thailand, Uruguay Botswana, Cameroon, Chad, Congo Dem. Rep., Cote d'Ivoire, Lesotho, Mozambique, Rwanda, South Africa, Swaziland, Togo, Uganda, Zambia Efficiency oriented (23 countries) Argentina, Belize, Cambodia, Colombia, El Salvador, Guatemala, Honduras, Indonesia, Iran, Lao RDR, Latvia, Nepal, Niger, Romania, Senegal, Vietnam Angola, Benin, Burkina Faso, Central African Republic, Eritrea, Haiti, Tanzania 14

15. Conclusions 3 Addressing countries’ harsh environment is helpful in controlling HIV/AIDS –if countries achieved a notable* increase in “voice and accountability,” the efficiency of their HIV/AIDS programs would increase by 40.8%. –For countries in the lowest quartile of per capita gross national income (GNI), a notable* increase in GNI would increase the efficiency of their AIDS programs by 45.0%. *A “notable” increase is defined as change from the lowest 25 th percentile to the average value of a variable 15

16. Conclusions 4 Low-income countries with high HIV/AIDS prevalence remain the targets for controlling the spread of HIV/AIDS –Low income countries share most of HIV/AIDS burden –Low level of governance in those countries implies significant room for improvement of efficiency 16

17. Relationship between gross national income and government effectiveness 17

18. Conclusion 5 Controlling HIV/AIDS requires health sector actions beyond HIV/AIDS –Increase government commitment to health –Strengthen health care system 18

19. Conclusion 6 Controlling HIV/AIDS requires multisectoral cooperation beyond the health sector –Strengthen governance –Alleviate poverty 19

20. Limitations DEA highly sensitive to data accuracy Input and outputs assumed representative Quality of services not measured Lag effect of inputs not considered 20

21. 21 Acknowledgements Joan Kaufman, ScD, Brandeis University John Stover, Futures Institute

22. 22 Contact: Shepard@brandeis.edu Wuzengcn@brandeis.edu