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Sub optimal HIV status ascertainment at antenatal clinics and the impact on HIV prevalence estimates: A cross sectional study

BACKGROUND: While many countries including Kenya transitioned from sentinel surveillance to the use of routine antenatal care (ANC) data to estimate the burden of HIV, countries in Sub Saharan Africa reported several challenges of this transition, including low uptake of HIV testing and sub national...

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Autores principales: Wangara, Fatihiyya, Estill, Janne, Kipruto, Hillary, Wools-Kaloustian, Kara, Chege, Wendy, Manguro, Griffins, Keiser, Olivia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714869/
https://www.ncbi.nlm.nih.gov/pubmed/36454873
http://dx.doi.org/10.1371/journal.pone.0278450
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author Wangara, Fatihiyya
Estill, Janne
Kipruto, Hillary
Wools-Kaloustian, Kara
Chege, Wendy
Manguro, Griffins
Keiser, Olivia
author_facet Wangara, Fatihiyya
Estill, Janne
Kipruto, Hillary
Wools-Kaloustian, Kara
Chege, Wendy
Manguro, Griffins
Keiser, Olivia
author_sort Wangara, Fatihiyya
collection PubMed
description BACKGROUND: While many countries including Kenya transitioned from sentinel surveillance to the use of routine antenatal care (ANC) data to estimate the burden of HIV, countries in Sub Saharan Africa reported several challenges of this transition, including low uptake of HIV testing and sub national / site-level differences in HIV prevalence estimates. In Kenya voluntary HIV testing is offered to all 1(st) ANC clients. However, some women may decline testing. We aim to predict the HIV positivity (as a proxy of prevalence) at ANC assuming 100% uptake of HIV testing and compare this to the observed positivity. METHODS: Using a cross sectional study design, we examine routine data on HIV testing among all women attending ANC in Kwale County, Kenya, for the period January 2015 to December 2019.We used a generalized estimating equation with binomial distribution to model the observed HIV prevalence as explained by HIV status ascertainment. We then used marginal standardization to predict the HIV prevalence at 100% HIV status ascertainment and make recommendations to improve the utility of ANC routine data for HIV surveillance. RESULTS: HIV testing at ANC was at 91.3%, slightly above the global target of 90%. If there was 100% HIV status ascertainment at ANC, the HIV prevalence would be 2.7% (95% CI 2.3–3.2). This was 0.3% lower than the observed prevalence. Across the yearly predictions, there was no difference between the observed and predicted values except for 2018 where the HIV prevalence was underestimated with an absolute bias of -0.2 percent. This implies missed opportunities for identifying new HIV infections in the year 2018. CONCLUSIONS: Imperfect HIV status ascertainment at ANC overestimates HIV prevalence among women attending ANC in Kwale County. However, the use of ANC routine data may underestimate the true population prevalence. There is need to address both community level and health facility level barriers to the uptake of ANC services.
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spelling pubmed-97148692022-12-02 Sub optimal HIV status ascertainment at antenatal clinics and the impact on HIV prevalence estimates: A cross sectional study Wangara, Fatihiyya Estill, Janne Kipruto, Hillary Wools-Kaloustian, Kara Chege, Wendy Manguro, Griffins Keiser, Olivia PLoS One Research Article BACKGROUND: While many countries including Kenya transitioned from sentinel surveillance to the use of routine antenatal care (ANC) data to estimate the burden of HIV, countries in Sub Saharan Africa reported several challenges of this transition, including low uptake of HIV testing and sub national / site-level differences in HIV prevalence estimates. In Kenya voluntary HIV testing is offered to all 1(st) ANC clients. However, some women may decline testing. We aim to predict the HIV positivity (as a proxy of prevalence) at ANC assuming 100% uptake of HIV testing and compare this to the observed positivity. METHODS: Using a cross sectional study design, we examine routine data on HIV testing among all women attending ANC in Kwale County, Kenya, for the period January 2015 to December 2019.We used a generalized estimating equation with binomial distribution to model the observed HIV prevalence as explained by HIV status ascertainment. We then used marginal standardization to predict the HIV prevalence at 100% HIV status ascertainment and make recommendations to improve the utility of ANC routine data for HIV surveillance. RESULTS: HIV testing at ANC was at 91.3%, slightly above the global target of 90%. If there was 100% HIV status ascertainment at ANC, the HIV prevalence would be 2.7% (95% CI 2.3–3.2). This was 0.3% lower than the observed prevalence. Across the yearly predictions, there was no difference between the observed and predicted values except for 2018 where the HIV prevalence was underestimated with an absolute bias of -0.2 percent. This implies missed opportunities for identifying new HIV infections in the year 2018. CONCLUSIONS: Imperfect HIV status ascertainment at ANC overestimates HIV prevalence among women attending ANC in Kwale County. However, the use of ANC routine data may underestimate the true population prevalence. There is need to address both community level and health facility level barriers to the uptake of ANC services. Public Library of Science 2022-12-01 /pmc/articles/PMC9714869/ /pubmed/36454873 http://dx.doi.org/10.1371/journal.pone.0278450 Text en © 2022 Wangara et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wangara, Fatihiyya
Estill, Janne
Kipruto, Hillary
Wools-Kaloustian, Kara
Chege, Wendy
Manguro, Griffins
Keiser, Olivia
Sub optimal HIV status ascertainment at antenatal clinics and the impact on HIV prevalence estimates: A cross sectional study
title Sub optimal HIV status ascertainment at antenatal clinics and the impact on HIV prevalence estimates: A cross sectional study
title_full Sub optimal HIV status ascertainment at antenatal clinics and the impact on HIV prevalence estimates: A cross sectional study
title_fullStr Sub optimal HIV status ascertainment at antenatal clinics and the impact on HIV prevalence estimates: A cross sectional study
title_full_unstemmed Sub optimal HIV status ascertainment at antenatal clinics and the impact on HIV prevalence estimates: A cross sectional study
title_short Sub optimal HIV status ascertainment at antenatal clinics and the impact on HIV prevalence estimates: A cross sectional study
title_sort sub optimal hiv status ascertainment at antenatal clinics and the impact on hiv prevalence estimates: a cross sectional study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714869/
https://www.ncbi.nlm.nih.gov/pubmed/36454873
http://dx.doi.org/10.1371/journal.pone.0278450
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