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HIV prevalence, testing and treatment among men who have sex with men through engagement in virtual sexual networks in Kenya: a cross‐sectional bio‐behavioural study

INTRODUCTION: In Kenya, men who have sex with men (MSM) are increasingly using virtual sites, including web‐based apps, to meet sex partners. We examined HIV testing, HIV prevalence, awareness of HIV‐positive status and linkage to antiretroviral therapy (ART), for HIV‐positive MSM who solely met par...

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Detalles Bibliográficos
Autores principales: Bhattacharjee, Parinita, Isac, Shajy, Musyoki, Helgar, Emmanuel, Faran, Olango, Kennedy, Kuria, Samuel, Ongaro, Martin K, Walimbwa, Jeffrey, Musimbi, Janet, Mugambi, Mary, Kaosa, Shem, Kioko, Japheth, Njraini, Margret, Melon, Memory, Onyoni, Juddie, Bartilol, Kigen, Becker, Marissa, Lorway, Robert, Pickles, Michael, Moses, Stephen, Blanchard, James, Mishra, Sharmistha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319161/
https://www.ncbi.nlm.nih.gov/pubmed/32589341
http://dx.doi.org/10.1002/jia2.25516
Descripción
Sumario:INTRODUCTION: In Kenya, men who have sex with men (MSM) are increasingly using virtual sites, including web‐based apps, to meet sex partners. We examined HIV testing, HIV prevalence, awareness of HIV‐positive status and linkage to antiretroviral therapy (ART), for HIV‐positive MSM who solely met partners via physical sites (PMSM), compared with those who did so in virtual sites (either solely via virtual sites (VMSM), or via both virtual and physical sites (DMSM)). METHODS: We conducted a cross‐sectional bio‐behavioural survey of 1200 MSM, 15 years and above, in three counties in Kenya between May and July 2019, using random sampling of physical and virtual sites. We classified participants as PMSM, DMSM and VMSM, based on where they met sex partners, and compared the following between groups using chi‐square tests: (i) proportion tested; (ii) HIV prevalence and (iii) HIV care continuum among MSM living with HIV. We then performed multivariable logistic regression to measure independent associations between network engagement and HIV status. RESULTS: 177 (14.7%), 768 (64.0%) and 255 (21.2%), of participants were classified as PMSM, DMSM and VMSM respectively. 68.4%, 70.4% and 78.5% of PMSM, DMSM and VMSM, respectively, reported an HIV test in the previous six months. HIV prevalence was 8.5% (PMSM), 15.4% (DMSM) and 26.7% (VMSM), p < 0.001. Among those living with HIV, 46.7% (PMSM), 41.5% (DMSM) and 29.4% (VMSM) were diagnosed and aware of their status; and 40.0%, 35.6% and 26.5% were on antiretroviral treatment. After adjustment for other predictors, MSM engaged in virtual networks remained at a two to threefold higher risk of prevalent HIV: VMSM versus PMSM (adjusted odds ratio 3.88 (95% confidence interval (CI) 1.84 to 8.17) p < 0.001); DMSM versus PMSM (2.00 (95% CI 1.03 to 3.87), p = 0.040). CONCLUSIONS: Engagement in virtual networks is associated with elevated HIV risk, irrespective of individual‐level risk factors. Understanding the difference in characteristics among MSM‐seeking partners in different sites will help HIV programmes to develop subpopulation‐specific interventions.