Universal HIV testing and immediate treatment of HIV-infected individuals could dramatically reduce the HIV epidemic, yet HIV testing uptake in sub-Saharan Africa remains low. In Tanzania, despite improved availability of HIV testing options, nearly two thirds of adults have never tested for HIV. Novel HIV testing options specifically designed to match the preferences of high-risk and hard-to-reach populations hold the potential to improve the acceptability and uptake of HIV testing. To extend our previous work, which assessed uptake of HIV voluntary counseling and testing (VCT) across varied venues in the Kilimanjaro Region of Tanzania (free-standing, mobile, home-based, and clinic-based VCT), we propose to apply an innovative method for preference elicitation known as Discrete Choice Experiments (DCEs, sometimes referred to as conjoint analysis) to HIV testing in this region. Grounded in the economic theory of utility maximization, the DCE method identifies key modifiable features of HIV testing options, presents survey respondents with various combinations of these features (each representing a hypothetical HIV testing option), and asks them to choose their preferred alternatives. Responses are analyzed to estimate the relative value placed on individual testing features, and to determine what combinations of features most influence decision-making and uptake. The primary aims of this two-year study are to: 1) Use qualitative methods to identify key modifiable features of HIV testing programs that influence testing decisions;2) Develop a DCE survey and elicit preferences from 800 randomly selected residents of the Kilimanjaro Region of Tanzania;and 3) Estimate preferences for existing as well as hypothetical, but feasible, HIV testing interventions. Differences in testig preferences between persons who have never tested for HIV and those who have previously tested for HIV will be described. The study will be implemented in the Kilimanjaro Region of Tanzania by a multidisciplinary research team that combines a track record of successful HIV testing research in Tanzania and experience with DCEs in diverse fields. The DCE method, applied in this context, holds promise to identify HIV testing preferences of hard-to-reach and at-risk populations for whom customized testing interventions can be devised. The data from this study will form the basis for implementation research on the benefits of tailoring HIV testing interventions to the specific preferences of the intended target populations. The effectiveness and cost- effectiveness of such interventions can subsequently be evaluated in a randomized controlled trial. Adapting available testing options to heterogeneous communities in sub-Saharan Africa has the potential to broadly improve the uptake of HIV testing, thereby bringing more persons living with HIV/AIDS into care and equipping persons living without HIV/AIDS with important information about HIV prevention.
Despite worldwide efforts to promote HIV testing, rates of testing remain low. Adapting available testing options to the preferences of heterogeneous communities in sub-Saharan Africa has the potential to broadly improve uptake of HIV testing, thereby bringing more persons living with HIV into care and equipping persons living without HIV with important information about HIV prevention. This study applies Discrete Choice Experiments to identify preferences for existing and novel HIV testing options among hard-to-reach and high- risk populations in the Kilimanjaro Region of Tanzania.
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|Ostermann, Jan; Njau, Bernard; Mtuy, Tara et al. (2015) One size does not fit all: HIV testing preferences differ among high-risk groups in Northern Tanzania. AIDS Care 27:595-603|
|Ostermann, Jan; Njau, Bernard; Brown, Derek S et al. (2014) Heterogeneous HIV testing preferences in an urban setting in Tanzania: results from a discrete choice experiment. PLoS One 9:e92100|
|Njau, Bernard; Ostermann, Jan; Brown, Derek et al. (2014) HIV testing preferences in Tanzania: a qualitative exploration of the importance of confidentiality, accessibility, and quality of service. BMC Public Health 14:838|