1. Assessment of PEPFAR’s Impact on Selected Health System Parameters in Sub-Saharan African Countries Presented by: Anya Shen Viviane D. Lima, Wendy Zhang, Carly Heung, Alexis Palmer, Julio Montaner, Robert Hogg, Nathan Ford, Edward Mills MOAE0101

2. Overview PEPFAR results by September 2008  Supported treatment for more than 2.1 million people  Overall HIV prevention estimates unknown. Estimated 240,000 mother-to-child transmissions averted  10.1 million people received care globally Other published studies  Decreased HIV-related deaths in PEPFAR focus countries in Sub-Saharan Africa comparing to other countries in the same region 1 ‘The President’s Emergency Plan for AIDS Relief in Africa: An Evaluation of Outcomes’ Bendavid, et all. 2009

3. Research Objectives PEPFAR is a vertical program There is a need to investigate the effect that disease- specific vertical programs have on health systems and population health The objective: –Assessment of PEPFAR’s impact on selected population health parameters in Sub-Saharan African countries

4. Methods Focus countries: Botswana, Cote d’lvoire, Ethiopia, Kenya, Mozambique, Namibia, Nigeria, Rwanda, South Africa, Tanzania, Uganda, Zambia Control countries: Angola, Benin, Burkina Faso, Burundi, Cameroon, Central African Republic, Chad, Congo, Democratic Republic of Congo, Djibouti, Eritrea, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Lesotho, Liberia, Madagascar, Malawi, Mali, Niger, Senegal, Sierra Leone, Somalia, Sudan, Swaziland, Togo, Zimbabwe Focus Control

5. Methods Longitudinal data collected from WHO, UN, World Bank, US Census Bureau Time frame 1.Pre-PEPFAR era [1999-2002] 2.PEPFAR era [2004-2007] Comparison of trends in focus and control countries before and after the initiation of PEPFAR programs Mixed-effects Models, General Linear Regression Models

6. Mean Change between Pre- PEPFAR era and PEPFAR era, CI Comparison of Mean Change between Focus and Control, CI* P-value Focus-10.76 (-13.49, -8.03 )*-5.14(-0.63, -9.66)*P=.0028 Control-5.62(-7.40, -3.83)*

7. Average Change between Pre-PEPFAR era and PEPFAR era, CI Comparison of Average Change between Focus and Control, CI P-value Focus-3.18 (-5.50, -0.86)*1.61(-2.21, 5.42)P=.246 Control-4.79(-6.28, -3.29)*

8. Average Change between Pre-PEPFAR era and PEPFAR era, CI Comparison of Average Change between Focus and Control, CI P-value Focus-43.46 (-68.21, -18.71 )*-6.58(-47.26, 34.09)P=.653 Control-36.88 (-52.80, -20.95)*

9. Average Change between Pre-PEPFAR era and PEPFAR era, CI Comparison of Average Change between Focus and Control, CI P-value Focus0.42 (-0.20, 1.04)-0.08 (-1.10, 0.94)P=.825 Control0.50 (0.10, 0.90)*

10. Pre-PEPAR Mean Annual Change (1999-2002) PEPFAR Mean Annual Change (2004-2007) Difference in Mean Annual Change between Two Eras* Focus-0.30(-0.65, -0.05)*0.81(0.52, 1.10)*1.11(0.57, 1.75)* Control0.18(0.04, 0.41)*0.45(0.37, 0.54)*0.27(-0.04, 0.50)

11. PRE-PEPFAR Mean Annual Change (1999-2002) PEPFAR Mean Annual Change (2004-2007) Difference in Mean Annual Change between Two Eras Focus2.95(-3.70 to 9.59)-2.52(-5.01 to -0.02)*-5.47(-14.60 to 3.68) Control-1.31(-6.41 to 3.80)3.26(-5.75 to 12.26)

12. Pre-PEPFAR Mean Annual Change (1999-2002) PEPFAR Mean Annual Change (2004-2007) Difference in Mean Annual Change between Two Eras Focus5.52(-2.09 to 13.12)-3.41(-6.22 to -0.60)*-8.93(-19.34 to -1.49)* Control-1.33(-7.21 to 4.55)2.64(-1.74 to 7.03)3.97(-2.81 to 14.24)

13. Pre-PEPFAR Mean Annual Change (1999-2002) PEPFAR Mean Annual Change (2004-2007) Difference in Mean Annual rate of Change between Two Eras Focus32.45(23.94, 40.97)*-13.21(-17.86, -8.57)*-45.66(-58.83, -32.51)* Control15.89(11.25, 20.53)*2.44(-0.30, 5.17)-13.45(-20.83, -6.08)*

14. Mean Annual Change (1999-2002) Mean Annual Change (2004-2007) Difference in Mean Annual Change between Two Eras Focus18.84(11.01, 26.67)*-8.36(-11.81, -4.90)*-27.20(-38.48, -15.91)* Control8.29(4.51, 12.08)*-0.20(-2.04, 1.63)*-8.49(-2.88, 14.12)*

15. Limitations Other confounders - Global Fund Countries not picked at random & significant baseline differences. Population-based survey estimates in resource limited countries have the potential for bias and problems with results based on aggregated measures. Lack of data in key indicators. Lack of continuous data.

16. Conclusion This analysis demonstrates the impact of PEPFAR funding on mortality rates & population health indicators in Sub-Saharan Africa A significantly improving trend is shown in U5MR and Life Expectancy in PEPFAR-focus countries when compared with control countries Positive trends are evident in maternal mortality (though non-sig) rates in focus countries from Pre- PEPFAR era to PEPFAR era.

17. Acknowledgement The author would like to thank Dr. Viviane D Lima and Wendy Zhang for their statistical support, co-authors and the rest of the BC Centre for Excellence staff for their support and encouragement. Special thanks to Dr. Edward Mills for his encouragement and guidance for without which this project would not have been started.