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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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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
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author 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
author_facet 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
author_sort Bhebhe, Lynnette
collection PubMed
description 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.
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spelling pubmed-94202702022-08-29 Epidemiological and viral characteristics of undiagnosed HIV infections in Botswana 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 BMC Infect Dis Research 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. BioMed Central 2022-08-28 /pmc/articles/PMC9420270/ /pubmed/36031617 http://dx.doi.org/10.1186/s12879-022-07698-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
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
Epidemiological and viral characteristics of undiagnosed HIV infections in Botswana
title Epidemiological and viral characteristics of undiagnosed HIV infections in Botswana
title_full Epidemiological and viral characteristics of undiagnosed HIV infections in Botswana
title_fullStr Epidemiological and viral characteristics of undiagnosed HIV infections in Botswana
title_full_unstemmed Epidemiological and viral characteristics of undiagnosed HIV infections in Botswana
title_short Epidemiological and viral characteristics of undiagnosed HIV infections in Botswana
title_sort epidemiological and viral characteristics of undiagnosed hiv infections in botswana
topic Research
url 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
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