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Epidemiological and viral characteristics of undiagnosed HIV infections in Botswana

BACKGROUND: HIV-1 is endemic in Botswana. The country’s primary challenge is identifying people living with HIV who are unaware of their status. We evaluated factors associated with undiagnosed HIV infection using HIV-1 phylogenetic, behavioural, and demographic data. METHODS: As part of the Botswan...

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Detalles Bibliográficos
Autores principales: Bhebhe, Lynnette, Moyo, Sikhulile, Gaseitsiwe, Simani, Pretorius-Holme, Molly, Yankinda, Etienne K., Manyake, Kutlo, Kgathi, Coulson, Mmalane, Mompati, Lebelonyane, Refeletswe, Gaolathe, Tendani, Bachanas, Pamela, Ussery, Faith, Letebele, Mpho, Makhema, Joseph, Wirth, Kathleen E., Lockman, Shahin, Essex, Max, Novitsky, Vlad, Ragonnet-Cronin, Manon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420270/
https://www.ncbi.nlm.nih.gov/pubmed/36031617
http://dx.doi.org/10.1186/s12879-022-07698-4
Descripción
Sumario:BACKGROUND: HIV-1 is endemic in Botswana. The country’s primary challenge is identifying people living with HIV who are unaware of their status. We evaluated factors associated with undiagnosed HIV infection using HIV-1 phylogenetic, behavioural, and demographic data. METHODS: As part of the Botswana Combination Prevention Project, 20% of households in 30 villages were tested for HIV and followed from 2013 to 2018. A total of 12,610 participants were enrolled, 3596 tested HIV-positive at enrolment, and 147 participants acquired HIV during the trial. Extensive socio-demographic and behavioural data were collected from participants and next-generation sequences were generated for HIV-positive cases. We compared three groups of participants: (1) those previously known to be HIV-positive at enrolment (n = 2995); (2) those newly diagnosed at enrolment (n = 601) and (3) those who tested HIV-negative at enrolment but tested HIV-positive during follow-up (n = 147). We searched for differences in demographic and behavioural factors between known and newly diagnosed group using logistic regression. We also compared the topology of each group in HIV-1 phylogenies and used a genetic diversity-based algorithm to classify infections as recent (< 1 year) or chronic (≥ 1 year). RESULTS: Being male (aOR = 2.23) and younger than 35 years old (aOR = 8.08) was associated with undiagnosed HIV infection (p < 0.001), as was inconsistent condom use (aOR = 1.76). Women were more likely to have undiagnosed infections if they were married, educated, and tested frequently. For men, being divorced increased their risk. The genetic diversity-based algorithm classified most incident infections as recent (75.0%), but almost none of known infections (2.0%). The estimated proportion of recent infections among new diagnoses was 37.0% (p < 0.001). CONCLUSION: Our results indicate that those with undiagnosed infections are likely to be young men and women who do not use condoms consistently. Among women, several factors were predictive: being married, educated, and testing frequently increased risk. Men at risk were more difficult to delineate. A sizeable proportion of undiagnosed infections were recent based on a genetic diversity-based classifier. In the era of “test and treat all”, pre-exposure prophylaxis may be prioritized towards individuals who self-identify or who can be identified using these predictors in order to halt onward transmission in time. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07698-4.