Simo Fotso A, Johnson C, Vautier A, Kouamé KB, Diop PM, Silhol R, Maheu-Giroux M, Boily MC, Rouveau N, Doumenc-Aïdara C, Baggaley R, Ehui E, Larmarange J. Routine programmatic data show a positive population-level impact of HIV self-testing: the case of Côte d'Ivoire and implications for implementation.
AIDS 2022;
36:1871-1879. [PMID:
35848584 PMCID:
PMC9594126 DOI:
10.1097/qad.0000000000003328]
[Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 06/29/2022] [Accepted: 07/04/2022] [Indexed: 02/04/2023]
Abstract
OBJECTIVES
We estimate the effects of ATLAS's HIV self-testing (HIVST) kit distribution on conventional HIV testing, diagnoses, and antiretroviral treatment (ART) initiations in Côte d'Ivoire.
DESIGN
Ecological study using routinely collected HIV testing services program data.
METHODS
We used the ATLAS's programmatic data recorded between the third quarter of 2019 and the first quarter of 2021, in addition to data from the President's Emergency Plan for AIDS Relief dashboard. We performed ecological time series regression using linear mixed models. Results are presented per 1000 HIVST kits distributed through ATLAS.
RESULTS
We found a negative but nonsignificant effect of the number of ATLAS' distributed HIVST kits on conventional testing uptake (-190 conventional tests; 95% confidence interval [CI]: -427 to 37). The relationship between the number of HIVST kits and HIV diagnoses was significant and positive (+8 diagnosis; 95% CI: 0 to 15). No effect was observed on ART initiation (-2 ART initiations; 95% CI: -8 to 5).
CONCLUSIONS
ATLAS' HIVST kit distribution had a positive impact on HIV diagnoses. Despite the negative signal on conventional testing, even if only 20% of distributed kits are used, HIVST would increase access to testing. The methodology used in this paper offers a promising way to leverage routinely collected programmatic data to estimate the effects of HIVST kit distribution in real-world programs.
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