Share

The cost effectiveness and optimal configuration of oral HIV self-test kit distribution in South Africa: a model analysis

Title
The cost effectiveness and optimal configuration of oral HIV self-test kit distribution in South Africa: a model analysis
Presenter
Lise Jamieson
Authors
L. Jamieson * (1), L. Johnson (2), K. Matsimela (1), L. Sande (3), M. d'Elbée (3), M. Majam (4), T. Chidarikire (5), K. Hatzold (6), C. Johnson (7), F. Terris-Prestholt (3,8), B. Nichols (1,9,10), G. Meyer-Rath (1,9)
Institutions
(1) Health Economics and Epidemiology Research Office (HE2RO), Department of Internal Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa, (2) Centre of Infectious Disease Epidemiology and Research (CIDER), University of Cape Town, Cape Town, South Africa, (3) London School of Hygiene and Tropical Medicine, London, United Kingdom, (4) Ezintsha, Wits Reproductive Health and HIV Research Institute, University of the Witwatersrand, Johannesburg, South Africa, (5) National Department of Health, Pretoria, South Africa, (6) Population Sciences International, Cape Town, South Africa, (7) Global HIV, Hepatitis, STI Programmes, World Health Organization, Geneva, Switzerland, (8) UNAIDS, Geneva, Switzerland, (9) School of Public Health, Boston University, Department of Global Health, Boston, United States, (10) Amsterdam University Medical Center, Department of Medical Microbiology, Amsterdam, Netherlands

BACKGROUND: HIV self-testing (HIVST) has been shown to be acceptable, feasible and effective in increasing HIV testing uptake. Novel testing strategies are critical to achieving and maintaining the UNAIDS target of 95% HIV-positive diagnosis by 2030 in South Africa and globally.
METHODS: We modelled the impact of six HIVST distribution models (fixed-point, taxi ranks, workplace, partners of primary healthcare (PHC) index cases, partners of pregnant women, primary PHC distribution) in South Africa over 20years (2020-39), using data collected alongside the Self-Testing AfRica (STAR) Initiative. We modelled two coverage scenarios: A) 1 million HIVST kits (current) or B) up to 6.3 million kits (target) distributed annually. Incremental economic costs (2019USD) were estimated from the provider perspective; outcomes were based on surveys of a subset of kit recipients and modelled using the Thembisa model. We calculated the cost-effectiveness of each distribution model compared to the status-quo distribution configuration favouring primary PHC distribution, and optimised using a fractional factorial design.
RESULTS: The largest impact resulted from secondary distribution to partners of PHC index cases; however, it was one of the least cost-effective models (Figure 1). Workplace distribution was cost-saving ($52-$76 million), but had moderate epidemiological impact (Figure 1). Optimisation produced the largest epidemiological impact for the following distribution configurations: 50-70% through PHC index cases; 0-18% each through fixed point, taxi ranks, workplaces; 0-9% each through partners of pregnant women and primary distribution to PHC clients. An optimised scale-up of distribution to 6.3 million tests would result in a ~3-fold increase in life years saved (LYS) compared to a scale-up of current distribution patterns (216,000 vs 75,000 LYS).


CONCLUSIONS: Optimisation-informed distributions have the potential to vastly improve the impact of HIVST. Using this approach, HIVST can play a key role in improving the long-term health impact of investment in HIVST, and assist in catching up testing targets post-COVID-19.