How Much Demand for New HIV Prevention Technologies Can We Really Expect? Results from a Discrete Choice Experiment in South Africa

BACKGROUND For the first time in the history of HIV, new bio-medical interventions have been shown to be effective in preventing HIV transmission. For these new HIV prevention technologies (NPTs) to have an impact on the epidemic, they must be widely used. This study uses a discrete choice experiment (DCE) to: understand the relative strength of women's preferences for product characteristics, understand the implications for substitution away from male condoms, and inform realistic modelling of their potential impact and cost-effectiveness. METHODS A DCE was conducted among 1017 women in urban South Africa. Women were presented with choices between potential women's NPTs (microbicides, diaphragm, female condom) and 'what I did last time' (use or not use a condom) with different HIV and pregnancy prevention effectiveness' and prices. Choice probabilities are estimated using the nested logit model and used to predict uptake. RESULTS In this high HIV prevalence setting, HIV prevention effectiveness is the main driver of uptake followed by pregnancy prevention effectiveness. For example a microbicide with poor effectiveness would have niche appeal at just 11% predicted uptake, while a highly effective microbicide (95% effective against HIV and pregnancy) would have far wider appeal (56% predicted uptake). Though women who reported not using condoms were more likely to choose the NPTs, at current very high rates of male condom use in South Africa (60%), about half of microbicide uptake is projected to be among those currently not using condoms. CONCLUSIONS Women are very interested in NPTs, especially if highly effective in preventing HIV and pregnancy. Women in greatest need were also most likely to switch to the new products. Where products are not yet available for distribution, proxy data, such as that generated by DCEs, can bring realism to overly optimistic uptake scenarios found in many current impact models.