FRAC0106 | Impacts of financial incentives and male-targeted app on young female HIV incidence and male HIV-related mortality: a cluster randomized trial

Maxime Inghels¹, Hae-Young Kim^2|3, Thulile Mathenjwa², Maryam Shahmanesh⁴, Janet Seeley⁵, Sally Wyke⁶, Philippa Matthews⁴, Oluwafemi Adeagbo⁷, Dickman Gareta², Nuala Mcgrath⁹, H. Manisha Yapa⁹,Ann Blandford¹⁰, Thembelihle Zuma², Adrian Dobra¹¹, Till Bärnighausen¹², Frank Frank Tanser¹³ | ¹Lincoln Institute for Coastal and Rural Health, University of Lincoln, Lincoln, UK; ²Africa Health Research Institute, Durban, South Africa; ³Department of Population Health, New York University School of Medicine, New York, USA; ⁴Institute for Global Health, University College London, London, UK; ⁵Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, UK; ⁶School of Social and Political Sciences, School of Health and Wellbeing, University of Glasgow, Glasgow, UK; ⁷Department of Sociology, University of Johannesburg, Johannesburg, South Africa; ⁸Department of Social Statistics and Demography, Faculty of Social Sciences, University of Southampton, Southampton, UK; ⁹Westmead Clinical School, Faculty of Medicine & Health, University of Sydney, Sydney, Australia; ¹⁰University College London Interaction Centre, University College London, London, UK; ¹¹University of Washington, Seattle, USA; ¹²Heidelberg Institute of Global Health (HIGH), Heidelberg University, Heidelberg, Germany; ¹³Centre for Epidemic Response and Innovation, School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa

In 2018, 45 communities were randomized into four groups using a 2x2 factorial design: (i) CFIs for testing and linkage to care within 6 weeks (R50/US$3 food voucher); (ii) EPIC-HIV, based on self-determination theory; (iii) both CFI and EPIC-HIV; and (iv) standard of care. EPIC-HIV included two components: EPIC-HIV 1 (pre-test app for men) and EPIC-HIV 2 (post-diagnosis app for men who had not linked to care after one month). HIV-related mortality among men and HIV incidence among women aged 15–30 were assessed in the trial area during the 2015–2021 period. Incidence was measured among women with at least one documented HIV-negative test. Intervention effects were estimated using difference-in-differences analyses to compare the period pre-intervention (2015-2018) vs. post-intervention (2019-2021) using mixed-effects generalized Poisson regression models with robust variance estimation. Between 2015 and 2021, 2,976 men living with HIV and 5,760 women aged 15–30 were followed. Among those followed during the 2019-2021 period, 35.2% (835/2375) of men living with HIV and 56.9% (1115/1961) of young women had participated in the trial. HIV-related male mortality declined from 2.10 (173/8,224 person-years) to 1.97 (123/6,238 person-years), and HIV incidence among young women dropped from 6.23 (777/12,471 person-years) to 2.01 (82/4,081 person-years). However, compared to the standard of care arm, declines did not significantly differ across trial arms for HIV-related male mortality (CFI: aRR 1.84 [0.93-3.66], EPIC-HIV: aRR 1.45 [0.74-2.84], CFI + EPIC-HIV: aRR 1.33 [0.65-2.71]) and HIV incidence among young women (CFI: aRR 0.78 [0.15-4.09], EPIC-HIV: aRR 1.32 [0.36-4.88], CFI + EPIC-HIV: aRR 0.36 [0.07-1.89]). A one-time intervention combining CFIs and a male-focused decision-support app delivered at home did not significantly reduce long-term HIV-related mortality among men or HIV incidence among young women.