Cargando…

Identifying Risk Factors for Recent HIV Infection in Kenya Using a Recent Infection Testing Algorithm: Results from a Nationally Representative Population-Based Survey

INTRODUCTION: A recent infection testing algorithm (RITA) that can distinguish recent from long-standing HIV infection can be applied to nationally representative population-based surveys to characterize and identify risk factors for recent infection in a country. MATERIALS AND METHODS: We applied a...

Descripción completa

Detalles Bibliográficos
Autores principales: Kim, Andrea A., Parekh, Bharat S., Umuro, Mamo, Galgalo, Tura, Bunnell, Rebecca, Makokha, Ernest, Dobbs, Trudy, Murithi, Patrick, Muraguri, Nicholas, De Cock, Kevin M., Mermin, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4873043/
https://www.ncbi.nlm.nih.gov/pubmed/27195800
http://dx.doi.org/10.1371/journal.pone.0155498
_version_ 1782432827469463552
author Kim, Andrea A.
Parekh, Bharat S.
Umuro, Mamo
Galgalo, Tura
Bunnell, Rebecca
Makokha, Ernest
Dobbs, Trudy
Murithi, Patrick
Muraguri, Nicholas
De Cock, Kevin M.
Mermin, Jonathan
author_facet Kim, Andrea A.
Parekh, Bharat S.
Umuro, Mamo
Galgalo, Tura
Bunnell, Rebecca
Makokha, Ernest
Dobbs, Trudy
Murithi, Patrick
Muraguri, Nicholas
De Cock, Kevin M.
Mermin, Jonathan
author_sort Kim, Andrea A.
collection PubMed
description INTRODUCTION: A recent infection testing algorithm (RITA) that can distinguish recent from long-standing HIV infection can be applied to nationally representative population-based surveys to characterize and identify risk factors for recent infection in a country. MATERIALS AND METHODS: We applied a RITA using the Limiting Antigen Avidity Enzyme Immunoassay (LAg) on stored HIV-positive samples from the 2007 Kenya AIDS Indicator Survey. The case definition for recent infection included testing recent on LAg and having no evidence of antiretroviral therapy use. Multivariate analysis was conducted to determine factors associated with recent and long-standing infection compared to HIV-uninfected persons. All estimates were weighted to adjust for sampling probability and nonresponse. RESULTS: Of 1,025 HIV-antibody-positive specimens, 64 (6.2%) met the case definition for recent infection and 961 (93.8%) met the case definition for long-standing infection. Compared to HIV-uninfected individuals, factors associated with higher adjusted odds of recent infection were living in Nairobi (adjusted odds ratio [AOR] 11.37; confidence interval [CI] 2.64–48.87) and Nyanza (AOR 4.55; CI 1.39–14.89) provinces compared to Western province; being widowed (AOR 8.04; CI 1.42–45.50) or currently married (AOR 6.42; CI 1.55–26.58) compared to being never married; having had ≥ 2 sexual partners in the last year (AOR 2.86; CI 1.51–5.41); not using a condom at last sex in the past year (AOR 1.61; CI 1.34–1.93); reporting a sexually transmitted infection (STI) diagnosis or symptoms of STI in the past year (AOR 1.97; CI 1.05–8.37); and being aged <30 years with: 1) HSV-2 infection (AOR 8.84; CI 2.62–29.85), 2) male genital ulcer disease (AOR 8.70; CI 2.36–32.08), or 3) lack of male circumcision (AOR 17.83; CI 2.19–144.90). Compared to HIV-uninfected persons, factors associated with higher adjusted odds of long-standing infection included living in Coast (AOR 1.55; CI 1.04–2.32) and Nyanza (AOR 2.33; CI 1.67–3.25) provinces compared to Western province; being separated/divorced (AOR 1.87; CI 1.16–3.01) or widowed (AOR 2.83; CI 1.78–4.45) compared to being never married; having ever used a condom (AOR 1.61; CI 1.34–1.93); and having a STI diagnosis or symptoms of STI in the past year (AOR 1.89; CI 1.20–2.97). Factors associated with lower adjusted odds of long-standing infection included using a condom at last sex in the past year (AOR 0.47; CI 0.36–0.61), having no HSV2-infection at aged <30 years (AOR 0.38; CI 0.20–0.75) or being an uncircumcised male aged <30 years (AOR 0.30; CI 0.15–0.61). CONCLUSION: We identified factors associated with increased risk of recent and longstanding HIV infection using a RITA applied to blood specimens collected in a nationally representative survey. Though some false-recent cases may have been present in our sample, the correlates of recent infection identified were epidemiologically and biologically plausible. These methods can be used as a model for other countries with similar epidemics to inform targeted combination prevention strategies aimed to drastically decrease new infections in the population.
format Online
Article
Text
id pubmed-4873043
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-48730432016-06-09 Identifying Risk Factors for Recent HIV Infection in Kenya Using a Recent Infection Testing Algorithm: Results from a Nationally Representative Population-Based Survey Kim, Andrea A. Parekh, Bharat S. Umuro, Mamo Galgalo, Tura Bunnell, Rebecca Makokha, Ernest Dobbs, Trudy Murithi, Patrick Muraguri, Nicholas De Cock, Kevin M. Mermin, Jonathan PLoS One Research Article INTRODUCTION: A recent infection testing algorithm (RITA) that can distinguish recent from long-standing HIV infection can be applied to nationally representative population-based surveys to characterize and identify risk factors for recent infection in a country. MATERIALS AND METHODS: We applied a RITA using the Limiting Antigen Avidity Enzyme Immunoassay (LAg) on stored HIV-positive samples from the 2007 Kenya AIDS Indicator Survey. The case definition for recent infection included testing recent on LAg and having no evidence of antiretroviral therapy use. Multivariate analysis was conducted to determine factors associated with recent and long-standing infection compared to HIV-uninfected persons. All estimates were weighted to adjust for sampling probability and nonresponse. RESULTS: Of 1,025 HIV-antibody-positive specimens, 64 (6.2%) met the case definition for recent infection and 961 (93.8%) met the case definition for long-standing infection. Compared to HIV-uninfected individuals, factors associated with higher adjusted odds of recent infection were living in Nairobi (adjusted odds ratio [AOR] 11.37; confidence interval [CI] 2.64–48.87) and Nyanza (AOR 4.55; CI 1.39–14.89) provinces compared to Western province; being widowed (AOR 8.04; CI 1.42–45.50) or currently married (AOR 6.42; CI 1.55–26.58) compared to being never married; having had ≥ 2 sexual partners in the last year (AOR 2.86; CI 1.51–5.41); not using a condom at last sex in the past year (AOR 1.61; CI 1.34–1.93); reporting a sexually transmitted infection (STI) diagnosis or symptoms of STI in the past year (AOR 1.97; CI 1.05–8.37); and being aged <30 years with: 1) HSV-2 infection (AOR 8.84; CI 2.62–29.85), 2) male genital ulcer disease (AOR 8.70; CI 2.36–32.08), or 3) lack of male circumcision (AOR 17.83; CI 2.19–144.90). Compared to HIV-uninfected persons, factors associated with higher adjusted odds of long-standing infection included living in Coast (AOR 1.55; CI 1.04–2.32) and Nyanza (AOR 2.33; CI 1.67–3.25) provinces compared to Western province; being separated/divorced (AOR 1.87; CI 1.16–3.01) or widowed (AOR 2.83; CI 1.78–4.45) compared to being never married; having ever used a condom (AOR 1.61; CI 1.34–1.93); and having a STI diagnosis or symptoms of STI in the past year (AOR 1.89; CI 1.20–2.97). Factors associated with lower adjusted odds of long-standing infection included using a condom at last sex in the past year (AOR 0.47; CI 0.36–0.61), having no HSV2-infection at aged <30 years (AOR 0.38; CI 0.20–0.75) or being an uncircumcised male aged <30 years (AOR 0.30; CI 0.15–0.61). CONCLUSION: We identified factors associated with increased risk of recent and longstanding HIV infection using a RITA applied to blood specimens collected in a nationally representative survey. Though some false-recent cases may have been present in our sample, the correlates of recent infection identified were epidemiologically and biologically plausible. These methods can be used as a model for other countries with similar epidemics to inform targeted combination prevention strategies aimed to drastically decrease new infections in the population. Public Library of Science 2016-05-19 /pmc/articles/PMC4873043/ /pubmed/27195800 http://dx.doi.org/10.1371/journal.pone.0155498 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Kim, Andrea A.
Parekh, Bharat S.
Umuro, Mamo
Galgalo, Tura
Bunnell, Rebecca
Makokha, Ernest
Dobbs, Trudy
Murithi, Patrick
Muraguri, Nicholas
De Cock, Kevin M.
Mermin, Jonathan
Identifying Risk Factors for Recent HIV Infection in Kenya Using a Recent Infection Testing Algorithm: Results from a Nationally Representative Population-Based Survey
title Identifying Risk Factors for Recent HIV Infection in Kenya Using a Recent Infection Testing Algorithm: Results from a Nationally Representative Population-Based Survey
title_full Identifying Risk Factors for Recent HIV Infection in Kenya Using a Recent Infection Testing Algorithm: Results from a Nationally Representative Population-Based Survey
title_fullStr Identifying Risk Factors for Recent HIV Infection in Kenya Using a Recent Infection Testing Algorithm: Results from a Nationally Representative Population-Based Survey
title_full_unstemmed Identifying Risk Factors for Recent HIV Infection in Kenya Using a Recent Infection Testing Algorithm: Results from a Nationally Representative Population-Based Survey
title_short Identifying Risk Factors for Recent HIV Infection in Kenya Using a Recent Infection Testing Algorithm: Results from a Nationally Representative Population-Based Survey
title_sort identifying risk factors for recent hiv infection in kenya using a recent infection testing algorithm: results from a nationally representative population-based survey
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4873043/
https://www.ncbi.nlm.nih.gov/pubmed/27195800
http://dx.doi.org/10.1371/journal.pone.0155498
work_keys_str_mv AT kimandreaa identifyingriskfactorsforrecenthivinfectioninkenyausingarecentinfectiontestingalgorithmresultsfromanationallyrepresentativepopulationbasedsurvey
AT parekhbharats identifyingriskfactorsforrecenthivinfectioninkenyausingarecentinfectiontestingalgorithmresultsfromanationallyrepresentativepopulationbasedsurvey
AT umuromamo identifyingriskfactorsforrecenthivinfectioninkenyausingarecentinfectiontestingalgorithmresultsfromanationallyrepresentativepopulationbasedsurvey
AT galgalotura identifyingriskfactorsforrecenthivinfectioninkenyausingarecentinfectiontestingalgorithmresultsfromanationallyrepresentativepopulationbasedsurvey
AT bunnellrebecca identifyingriskfactorsforrecenthivinfectioninkenyausingarecentinfectiontestingalgorithmresultsfromanationallyrepresentativepopulationbasedsurvey
AT makokhaernest identifyingriskfactorsforrecenthivinfectioninkenyausingarecentinfectiontestingalgorithmresultsfromanationallyrepresentativepopulationbasedsurvey
AT dobbstrudy identifyingriskfactorsforrecenthivinfectioninkenyausingarecentinfectiontestingalgorithmresultsfromanationallyrepresentativepopulationbasedsurvey
AT murithipatrick identifyingriskfactorsforrecenthivinfectioninkenyausingarecentinfectiontestingalgorithmresultsfromanationallyrepresentativepopulationbasedsurvey
AT muragurinicholas identifyingriskfactorsforrecenthivinfectioninkenyausingarecentinfectiontestingalgorithmresultsfromanationallyrepresentativepopulationbasedsurvey
AT decockkevinm identifyingriskfactorsforrecenthivinfectioninkenyausingarecentinfectiontestingalgorithmresultsfromanationallyrepresentativepopulationbasedsurvey
AT merminjonathan identifyingriskfactorsforrecenthivinfectioninkenyausingarecentinfectiontestingalgorithmresultsfromanationallyrepresentativepopulationbasedsurvey
AT identifyingriskfactorsforrecenthivinfectioninkenyausingarecentinfectiontestingalgorithmresultsfromanationallyrepresentativepopulationbasedsurvey