Potential population-level effects of HIV self-test distribution among key populations in Côte d'Ivoire, Mali, and Senegal: a mathematical modelling analysis

• Published in: The lancet HIV Vol. 11; no. 8; p. e531
• Main Authors: Silhol, Romain, Maheu-Giroux, Mathieu, Soni, Nirali, Simo Fotso, Arlette, Rouveau, Nicolas, Vautier, Anthony, Doumenc-Aïdara, Clémence, Geoffroy, Olivier, N'Guessan, Kouassi Noel, Sidibé, Younoussa, Kabemba, Odé Kanku, Gueye, Papa Alioune, Ndeye, Pauline Dama, Mukandavire, Christinah, Vickerman, Peter, Keita, Abdelaye, Ndour, Cheikh Tidiane, Larmarange, Joseph, Boily, Marie-Claude
• Format: Journal Article
• Language: English
• Published: Netherlands 01.08.2024
• Subjects: Adolescent; Adult; Cote d'Ivoire - epidemiology; Female; HIV Infections - diagnosis; HIV Infections - drug therapy; HIV Infections - epidemiology; HIV Infections - mortality; HIV Testing; Humans; Incidence; Male; Mali - epidemiology; Middle Aged; Models, Theoretical; Self-Testing; Senegal - epidemiology; Sex Workers - statistics & numerical data; Young Adult; Mali; Senegal; Cote d'Ivoire
• ISSN: 2352-3018
• DOI: 10.1016/S2352-3018(24)00126-7

During 2019-21, the AutoTest VIH, Libre d'accéder à la connaissance de son Statut (ATLAS) programme distributed around 380 000 HIV self-testing kits to key populations, including female sex workers, men who have sex with men, and their partners, in Côte d'Ivoire, Mali, and Senegal. We aimed to estimate the effects of the ATLAS programme and national scale-up of HIV self-test distribution on HIV diagnosis, HIV treatment coverage, HIV incidence, and HIV-related mortality. We adapted a deterministic compartmental model of HIV transmission in Côte d'Ivoire, parameterised and fitted to country-specific demographic, behavioural, HIV epidemiological, and intervention data in Côte d'Ivoire, Mali, and Senegal separately during 1980-2020. We simulated dynamics of new HIV infections, HIV diagnoses, and HIV-related deaths within scenarios with and without HIV self-test distribution among key populations. Models were separately parameterised and fitted to country-specific sets of epidemiological and intervention outcomes (stratified by sex, risk, age group, and HIV status, if available) over time within a Bayesian framework. We estimated the effects on the absolute increase in the proportion of people with HIV diagnosed at the end of 2021 for the ATLAS-only scenario and at the end of 2028 and 2038 for the HIV self-testing scale-up scenario. We estimated cumulative numbers of additional HIV diagnoses and initiations of antiretroviral therapy and the proportion and absolute numbers of new HIV infections and HIV-related deaths averted during 2019-21 and 2019-28 for the ATLAS-only scenario and during 2019-28 and 2019-38 for the HIV self-testing scale-up scenario. Our model estimated that ATLAS could have led to 700 (90% uncertainty interval [UI] 500-900) additional HIV diagnoses in Côte d'Ivoire, 500 (300-900) in Mali, and 300 (50-700) in Senegal during 2019-21, a 0·4 percentage point (90% UI 0·3-0·5) increase overall by the end of 2021. During 2019-28, ATLAS was estimated to avert 1900 (90% UI 1300-2700) new HIV infections and 600 (400-800) HIV-related deaths across the three countries, of which 38·6% (90% UI 31·8-48·3) of new infections and 70·1% (60·4-77·3) of HIV-related deaths would be among key populations. ATLAS would avert 1·5% (0·8-3·1) of all HIV-related deaths across the three countries during this period. Scaling up HIV self-testing would avert 16·2% (90% UI 10·0-23·1) of all new HIV infections during 2019-28 in Senegal, 5·3% (3·0-8·9) in Mali, and 1·6% (1·0-2·4) in Côte d'Ivoire. HIV self-testing scale-up among key populations was estimated to increase HIV diagnosis by the end of 2028 to 1·3 percentage points (90% UI 0·8-1·9) in Côte d'Ivoire, 10·6 percentage points (5·3-16·8) in Senegal, and 3·6 percentage points (2·0-6·4) in Mali. Scaling up HIV self-test distribution among key populations in western Africa could attenuate disparities in access to HIV testing and reduce infections and deaths among key populations and their partners. Unitaid, Solthis, the UK Medical Research Council Centre for Global Infectious Disease Analysis, the EU European & Developing Countries Clinical Trials Partnership programme, and the Wellcome Trust. For the French translation of the abstract see Supplementary Materials section.