Youth Preferences for HIV Testing in South Africa: Findings from the Youth Action for Health (YA4H) Study Using a Discrete Choice Experiment.

We conducted a discrete choice experiment (DCE) and quantified preferences for HIV testing among South African youth (Nov 2018 to Mar 2019). Six attributes and levels were identified through qualitative methods: source of HIV information; incentive amount and type; social support; testing method; and location. Each participant chose one of two options that comprised six attributes across 18 questions. Conditional logistic regression estimated the degree of preference [ß]. Of 130 participants, median age was 21 years (interquartile range 19-23 years), majority female (58%), and 85% previously tested for HIV. Testing alone over accompanied by a friend (ß = 0.22 vs. - 0.35; p < 0.01); SMS text over paper brochures (ß = 0.13 vs. - 0.10; p < 0.01); higher incentive values (R50) over no incentive (ß = 0.09 vs. - 0.07; p = 0.01); and food vouchers over cash (ß = 0.06 vs. ß = - 0.08; p = 0.01) were preferred. Testing at a clinic or home and family encouragement were important. Tailoring HTS to youth preferences may increase HIV testing.

Estimating non-communicable disease treatment costs using probability-based cost estimation.

The burden and impact of non-communicable diseases (NCDs) are well documented, accounting for 70% of premature deaths globally. In Sub-Saharan Africa, rising NCDs are estimated to account for 27% of mortality by 2020, a 4% increase from 2005. This increase will inevitably lead to a higher demand for NCD treatment services, exerting pressure on limited public financial resources. To get a sense of the resources required to treat NCDs, it is necessary to estimate the costs associated with the diagnosis, treatment and management thereof. Typically, in estimating costs for health services, countries use historical patient level data combined with demographic trend data and non-patient level data to arrive at estimated future costs. This methodology relies heavily on the availability of data from a wide variety of sources stretching beyond the health sector. Low-and-middle-income countries often lack the requisite data and are compelled to use less efficient ways to determine resource allocation. This study explores the use of probability-based cost estimation to estimate the cost of delivering NCD treatment services in South Africa, one such data-poor environment.Probability-based cost estimation, in combination with deterministic cost estimation, is used in arriving at a cost estimate for NCD treatment services at primary healthcare facility level. On its own, deterministic cost estimation can determine total costs, provided all the input variables are known. This is not always possible because of the lack of one or more input variables. In most instances, the lacking input variable is the quantities at which specific conditions will be treated. This problem is addressed by using probability-based cost estimation through which a mean cost is calculated and applied to the target population as a whole, eliminating the need for quantities per condition. Thus, this model contains both deterministic and probabilistic cost estimation elements.

Exploring perceptions of low risk behaviour and drivers to test for HIV among South African youth.

Human Immunodeficiency Virus (HIV) prevalence among South African youth is high, yet HIV testing remains suboptimal. We explored how perceptions of HIV risk and behaviours informed decisions to test for HIV. This study was conducted from April 2018 to March 2019 in Ekurhuleni district, Gauteng Province with males and females aged between 15-24 years. Twenty-five youth with unknown HIV status participated in in-depth interviews (IDIs); while four focus group discussions (FGDs) were conducted with those that previously tested for HIV. Probes used in the guides included types of incentives that youth would value when testing for HIV or receiving treatment; barriers and motivators to HIV testing; enablers and challenges to using cellphone technology and preferences on type of social media that could be used to create awareness about HIV testing services. IDIs and FGDs were audio-recorded, transcribed, and translated. QSR NVIVO 10 was used for the analysis. The majority of the youth perceived that their risk of HIV infection was low due to factors such as being young, lacking physical signs of HIV, being sexually inactive and parents not being HIV positive. However, youth identified high risk behaviours such as unprotected sex, multiple sexual partners, excessive drinking of alcohol, being victims of sexual abuse, road accidents and violent behaviour as increasing their vulnerability to HIV. Most youth highlighted cues to action that would motivate them to test for HIV such as support of parents, receiving incentives, improved confidentiality during HIV testing and receiving information about HIV via social media (Facebook, Twitter and Whatsapp). Despite perceptions of low risk to HIV, youth remain vulnerable to HIV. Disseminating HIV information via digital platforms; giving youth options to choose between testing locations that they consider to be private; providing incentives and equipping parents/guardians to encourage youth to test could optimise HIV testing.