School of Public Health an d Community Medicine Analysis of political governance as a determinant of ART coverage using country level data Man, W.Y.N. 1, Worth, H 1. Kelly, A. 2, Wilson, D. 3 & Siba, P. 2, 1 International HIV Research Group, University of New South Wales, Sydney, Australia 2 Papua New Guinea Institute of Medical Research, Papua New Guinea 3 Kirby Institute, University of New South Wales, Australia

Rationale and Method Considerable interest arisen in the role of governance or political commitment in determining success or failure of HIV/AIDS policies and programs, including roll-out of ART Aim of this project was to investigate governance as a determinant of ART roll-out in PNG (using country-level data) but grew bigger than that Collection of (low to middle income) country-level data on: Health burden and resources; socio-demography; economy; development; equality HIV prevalence; ART coverage (from UNAIDS/WHO databases, UNGASS reports) Indicators of political governance (World Bank)- political voice and accountability; political stability; control of corruption; government effectiveness; rule of law; regulatory quality; democracy scores (Polity IV Project) Study funded by the PNG AIDS Council

Statistical Model/Analysis/Results Outcome variables: ART coverage 2009 as % persons needing it (UNGASS Indicator 4) Baseline multi-level model for univariate analyses of each potential predictor of ART coverage. Variables with p<0.10 tested in multivariate multi-level model, and again in final model. Results show: Countries with higher levels of voice, accountability, lower regulatory quality, more political stability, better control of corruption have higher levels of ART coverage Control of corruption strongly associated with ART coverage Indicators of economic development dropped out when control of corruption was included in multivariate regression model Somalia, Myanmar, DR Congo, Chad, PNG,and Angola (with high levels of corruption) had relatively poor ART coverage Countries with better control of corruption (e.g. Chile, Uruguay and Botswana) had relatively better ART coverage

Predictors of percentage of ART coverage (logit-transformed; based on UNAIDS estimates; N=678). a Rescaled so that the plausible range is from 0 to10 (original plausible range was from 0 to 1). b χ 2 statistic is estimated from (F statistic)X(numerator degrees of freedom).