A discrete choice experiment investigating HIV testing preferences in South Africa.

ABSTRACT

BACKGROUND: South Africa (SA) has the world's highest burden of HIV infection, with an estimated 13.7% of the population living with HIV (PLWH/Persons Living With HIV). The early identification of PLWH and rapid engagement of them in HIV treatment are indispensable tools in the fight against HIV transmission. Understanding client preferences for HIV testing may help improve uptake. This study aimed to elicit client preferences for key characteristics of HIV testing options. METHODS: A discrete-choice experiment (DCE) was conducted among individuals presenting for HIV testing at two public primary healthcare facilities in Cape Town, South Africa. Participants were asked to make nine choices between two unlabeled alternatives that differed in five attributes, in line with previous DCEs conducted in Tanzania and Colombia testing availability, distance from the testing center, method for obtaining the sample, medication availability at testing centers, and confidentiality. Data were analyzed using a random parameter logit model. RESULTS: A total of 206 participants agreed to participate in the study, of whom 199 fully completed the choice tasks. The mean age of the participants was 33.6 years, and most participants were female (83%). Confidentiality was the most important attribute, followed by distance from the testing center and the method of obtaining a sample. Patients preferred finger prick to venipuncture as a method for obtaining the sample. Medication availability at the testing site was also preferred over a referral to an HIV treatment center for a positive HIV test. There were significant variations in preferences among respondents. CONCLUSION: In addition to accentuating the importance of confidentiality, the method for obtaining the sample and the location of sites for collection of medication should be considered in the testing strategy. The variations in preferences within target populations should be considered in identifying optimal testing strategies.