FIGURE 6-14b Differences between men and women on ART in baseline characteristics (7 countries, 165 clinics), 2004–2011.
NOTE: CD4 = cluster of differentiation 4; OI = opportunistic infection; TB = tuberculosis; WHO = World Health Organization.
SOURCE: Programmatic data provided by Track 1.0 partner.

direct plausible pathway to affect mortality is through PEPFAR’s support of HIV care and treatment programs.

Several recently published papers using statistical methods to address this question have compared PEPFAR focus countries to non-focus countries (Bendavid and Bhattacharya, 2009; Bendavid et al., 2012; Duber et al., 2010). The committee reviewed these analyses as one source of information to assess the impact of PEPFAR on HIV/AIDS. One of these analyses did not find an effect on health outcomes (Duber et al., 2010), perhaps due to timeframe and data limitations, but the other analyses indicated a measurable population health impact of PEPFAR on adult mortality in a subset of partner countries (Bendavid and Bhattacharya, 2009; Bendavid et al., 2012). However, none of the studies covered the full scope of countries included in this evaluation, and using non-focus countries as a control is problematic because, although they were not focus countries, they nonetheless received some level of PEPFAR funding. These studies also had other limitations related to the difficulty of evaluating a large, complex program retrospectively, such as limited data availability and quality and the difficulty of controlling for non-PEPFAR factors in the analyses.

During its deliberations, the committee explored the possibility of conducting its own modeling to evaluate the impact of PEPFAR. After careful consideration, the evaluation committee determined that within the scope, time, and resources of this evaluation it was not feasible to conduct statisti-

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