In 2015 around 15 million people living with HIV were receiving antiretroviral treatment (ART) in sub-Saharan Africa. Sustained provision of ART, though both prudent and necessary, creates substantial long-term fiscal obligations for countries affected by HIV/AIDS. As donor assistance for health remains constrained, novel financing mechanisms are needed to augment funding domestic sources. We explore how Innovative Financing has been used to co-finance domestic HIV/AIDS responses. Based on analysis of non-health sectors, we identify innovative financing instruments that could be used in the HIV response.

Launched in 2003, the US President’s Emergency Plan for AIDS Relief (PEPFAR) is the largest disease-focused assistance program in the world. We analyzed PEPFAR budgets for governance and systems for the period 2004-14 to ascertain whether PEPFAR’s stated emphasis on strengthening health systems has been manifested financially. The main outcome variable in our analysis, the first of its kind using these data, was the share of PEPFAR’s total annual budget for a country that was designated for governance and systems. The share of planned PEPFAR funding for governance and systems increased from 14.9 percent, on average, in 2004 to 27.5 percent in 2013, but it declined in 2014 to 20.8 percent. This study shows that the size of a country’s PEPFAR budget was negatively associated with the share allocated for governance and systems (compared with other budget program areas); it also shows that there was no significant relationship between budgets for governance and systems and HIV prevalence. It is crucial for the global health policy community to better understand how such investments are allocated and used for health systems strengthening.

Conventional estimators for the expected value of sample information (EVSI) are computationally expensive or limited to specific analytic scenarios. I describe a novel approach that allows efficient EVSI computation for a wide range of study designs and is applicable to models of arbitrary complexity.