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National HIV testing and diagnosis coverage in sub-Saharan Africa: a new modeling tool for estimating the ‘first 90’ from program and survey data

OBJECTIVE: HIV testing services (HTS) are a crucial component of national HIV responses. Learning one's HIV diagnosis is the entry point to accessing life-saving antiretroviral treatment and care. Recognizing the critical role of HTS, the Joint United Nations Programme on HIV/AIDS (UNAIDS) laun...

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Autores principales: Maheu-Giroux, Mathieu, Marsh, Kimberly, Doyle, Carla M., Godin, Arnaud, Lanièce Delaunay, Charlotte, Johnson, Leigh F., Jahn, Andreas, Abo, Kouamé, Mbofana, Francisco, Boily, Marie-Claude, Buckeridge, David L., Hankins, Catherine A., Eaton, Jeffrey W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6919235/
https://www.ncbi.nlm.nih.gov/pubmed/31764066
http://dx.doi.org/10.1097/QAD.0000000000002386
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author Maheu-Giroux, Mathieu
Marsh, Kimberly
Doyle, Carla M.
Godin, Arnaud
Lanièce Delaunay, Charlotte
Johnson, Leigh F.
Jahn, Andreas
Abo, Kouamé
Mbofana, Francisco
Boily, Marie-Claude
Buckeridge, David L.
Hankins, Catherine A.
Eaton, Jeffrey W.
author_facet Maheu-Giroux, Mathieu
Marsh, Kimberly
Doyle, Carla M.
Godin, Arnaud
Lanièce Delaunay, Charlotte
Johnson, Leigh F.
Jahn, Andreas
Abo, Kouamé
Mbofana, Francisco
Boily, Marie-Claude
Buckeridge, David L.
Hankins, Catherine A.
Eaton, Jeffrey W.
author_sort Maheu-Giroux, Mathieu
collection PubMed
description OBJECTIVE: HIV testing services (HTS) are a crucial component of national HIV responses. Learning one's HIV diagnosis is the entry point to accessing life-saving antiretroviral treatment and care. Recognizing the critical role of HTS, the Joint United Nations Programme on HIV/AIDS (UNAIDS) launched the 90-90-90 targets stipulating that by 2020, 90% of people living with HIV know their status, 90% of those who know their status receive antiretroviral therapy, and 90% of those on treatment have a suppressed viral load. Countries will need to regularly monitor progress on these three indicators. Estimating the proportion of people living with HIV who know their status (i.e. the ‘first 90’), however, is difficult. METHODS: We developed a mathematical model (henceforth referred to as ‘Shiny90’) that formally synthesizes population-based survey and HTS program data to estimate HIV status awareness over time. The proposed model uses country-specific HIV epidemic parameters from the standard UNAIDS Spectrum model to produce outputs that are consistent with other national HIV estimates. Shiny90 provides estimates of HIV testing history, diagnosis rates, and knowledge of HIV status by age and sex. We validate Shiny90 using both in-sample comparisons and out-of-sample predictions using data from three countries: Côte d’Ivoire, Malawi, and Mozambique. RESULTS: In-sample comparisons suggest that Shiny90 can accurately reproduce longitudinal sex-specific trends in HIV testing. Out-of-sample predictions of the fraction of people living with HIV ever tested over a 4-to-6-year time horizon are also in good agreement with empirical survey estimates. Importantly, out-of-sample predictions of HIV knowledge of status are consistent (i.e. within 4% points) with those of the fully calibrated model in the three countries when HTS program data are included. The model's predictions of knowledge of status are higher than available self-reported HIV awareness estimates, however, suggesting – in line with previous studies – that these self-reports could be affected by nondisclosure of HIV status awareness. CONCLUSION: Knowledge of HIV status is a key indicator to monitor progress, identify bottlenecks, and target HIV responses. Shiny90 can help countries track progress towards their ‘first 90’ by leveraging surveys of HIV testing behaviors and annual HTS program data.
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spelling pubmed-69192352020-03-10 National HIV testing and diagnosis coverage in sub-Saharan Africa: a new modeling tool for estimating the ‘first 90’ from program and survey data Maheu-Giroux, Mathieu Marsh, Kimberly Doyle, Carla M. Godin, Arnaud Lanièce Delaunay, Charlotte Johnson, Leigh F. Jahn, Andreas Abo, Kouamé Mbofana, Francisco Boily, Marie-Claude Buckeridge, David L. Hankins, Catherine A. Eaton, Jeffrey W. AIDS Editorial OBJECTIVE: HIV testing services (HTS) are a crucial component of national HIV responses. Learning one's HIV diagnosis is the entry point to accessing life-saving antiretroviral treatment and care. Recognizing the critical role of HTS, the Joint United Nations Programme on HIV/AIDS (UNAIDS) launched the 90-90-90 targets stipulating that by 2020, 90% of people living with HIV know their status, 90% of those who know their status receive antiretroviral therapy, and 90% of those on treatment have a suppressed viral load. Countries will need to regularly monitor progress on these three indicators. Estimating the proportion of people living with HIV who know their status (i.e. the ‘first 90’), however, is difficult. METHODS: We developed a mathematical model (henceforth referred to as ‘Shiny90’) that formally synthesizes population-based survey and HTS program data to estimate HIV status awareness over time. The proposed model uses country-specific HIV epidemic parameters from the standard UNAIDS Spectrum model to produce outputs that are consistent with other national HIV estimates. Shiny90 provides estimates of HIV testing history, diagnosis rates, and knowledge of HIV status by age and sex. We validate Shiny90 using both in-sample comparisons and out-of-sample predictions using data from three countries: Côte d’Ivoire, Malawi, and Mozambique. RESULTS: In-sample comparisons suggest that Shiny90 can accurately reproduce longitudinal sex-specific trends in HIV testing. Out-of-sample predictions of the fraction of people living with HIV ever tested over a 4-to-6-year time horizon are also in good agreement with empirical survey estimates. Importantly, out-of-sample predictions of HIV knowledge of status are consistent (i.e. within 4% points) with those of the fully calibrated model in the three countries when HTS program data are included. The model's predictions of knowledge of status are higher than available self-reported HIV awareness estimates, however, suggesting – in line with previous studies – that these self-reports could be affected by nondisclosure of HIV status awareness. CONCLUSION: Knowledge of HIV status is a key indicator to monitor progress, identify bottlenecks, and target HIV responses. Shiny90 can help countries track progress towards their ‘first 90’ by leveraging surveys of HIV testing behaviors and annual HTS program data. Lippincott Williams & Wilkins 2019-12-15 2019-11-11 /pmc/articles/PMC6919235/ /pubmed/31764066 http://dx.doi.org/10.1097/QAD.0000000000002386 Text en Copyright © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0
spellingShingle Editorial
Maheu-Giroux, Mathieu
Marsh, Kimberly
Doyle, Carla M.
Godin, Arnaud
Lanièce Delaunay, Charlotte
Johnson, Leigh F.
Jahn, Andreas
Abo, Kouamé
Mbofana, Francisco
Boily, Marie-Claude
Buckeridge, David L.
Hankins, Catherine A.
Eaton, Jeffrey W.
National HIV testing and diagnosis coverage in sub-Saharan Africa: a new modeling tool for estimating the ‘first 90’ from program and survey data
title National HIV testing and diagnosis coverage in sub-Saharan Africa: a new modeling tool for estimating the ‘first 90’ from program and survey data
title_full National HIV testing and diagnosis coverage in sub-Saharan Africa: a new modeling tool for estimating the ‘first 90’ from program and survey data
title_fullStr National HIV testing and diagnosis coverage in sub-Saharan Africa: a new modeling tool for estimating the ‘first 90’ from program and survey data
title_full_unstemmed National HIV testing and diagnosis coverage in sub-Saharan Africa: a new modeling tool for estimating the ‘first 90’ from program and survey data
title_short National HIV testing and diagnosis coverage in sub-Saharan Africa: a new modeling tool for estimating the ‘first 90’ from program and survey data
title_sort national hiv testing and diagnosis coverage in sub-saharan africa: a new modeling tool for estimating the ‘first 90’ from program and survey data
topic Editorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6919235/
https://www.ncbi.nlm.nih.gov/pubmed/31764066
http://dx.doi.org/10.1097/QAD.0000000000002386
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