Background: Youth in South Africa are disproportionately affected by STIs, HIV, and unintended pregnancies. Despite this, their uptake of HIV and contraceptive services remains a challenge. South Africa urgently needs tailored, scalable interventions to address both HIV infection and early pregnancy prevention for young people. These interventions generally take years to design, implement, and evaluate, leaving a gap. To that end, we have developed a framework to translate the expected impact of facility level attributes in increasing HIV/contraceptive service uptake for youth from a discrete choice experiment (DCE) into a cost effectiveness analysis (CEA).
Methods: We used a DCE (n=805) conducted in Gauteng, South Africa, which found that staff attitude, confidentiality, WiFi, subsidized food, afternoon hours and youth-only services were preferred attributes of health services. Based on this we simulated uptake of services adapted for these preferences. We divided preferences into modifiable attributes that could readily be adapted (e.g. WiFi), and non-modifiable (more nuanced attributes that are more challenging to cost and evaluate): staff attitude and estimated the incremental change in uptake of services using adapted services. Costs for modifiable preferences were estimated using data from two clinics in South Africa (2019 US$). We determined the incremental cost effectiveness ratio (ICER) of 15 intervention combinations, and report the results of interventions on the cost-effectiveness frontier.
Results: Greatest projected impact on uptake was from friendly and confidential services, both of which were considered non–modifiable (18.5% 95%CI:13.0-24.0%; 8.4% 95%CI:3.0-14.0% respectively). Modifiable factors on their own resulted in only small increases in expected uptake. (Food: 2.3% 95%CI:4.0%-9.00%; WiFi: 3.0% 95%CI: -4.0%-10.0%; Youth only services: 0.3% 95%CI: -6.0%-7.0%; Afternoon services: 0.8% 95%CI: -6.0%-7.0%). The order of interventions on the cost-effectiveness frontier are WiFi and youth-only services (ICER US$7.01- US$9.78), WiFi, youth-only services and food (ICER US$9.32 - US$10.45), followed by WiFi, youth-only services and extended afternoon hours (ICER US$14.46–US$43.63)
Conclusion: Combining DCE results and costing analyses within a modelling framework provides an innovative way to inform decisions on effective resource utilisation. Modifiable preferences, such as WiFi provision, youth only services and subsidized food, have potential to cost-effectively increase the proportion of youth accessing HIV and contraceptive services.