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A quantitative assessment of the consistency of projections from five mathematical models of the HIV epidemic in South Africa: a model comparison study

BACKGROUND: Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the robustness of estimates and highlight research gaps. As part of a larger project aiming to determine the optimal allocation of fundin...

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Autores principales: Moolla, Haroon, Phillips, Andrew, ten Brink, Debra, Mudimu, Edinah, Stover, John, Bansi-Matharu, Loveleen, Martin-Hughes, Rowan, Wulan, Nisaa, Cambiano, Valentina, Smith, Jennifer, Bershteyn, Anna, Meyer-Rath, Gesine, Jamieson, Lise, Johnson, Leigh F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612295/
https://www.ncbi.nlm.nih.gov/pubmed/37891514
http://dx.doi.org/10.1186/s12889-023-16995-9
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author Moolla, Haroon
Phillips, Andrew
ten Brink, Debra
Mudimu, Edinah
Stover, John
Bansi-Matharu, Loveleen
Martin-Hughes, Rowan
Wulan, Nisaa
Cambiano, Valentina
Smith, Jennifer
Bershteyn, Anna
Meyer-Rath, Gesine
Jamieson, Lise
Johnson, Leigh F.
author_facet Moolla, Haroon
Phillips, Andrew
ten Brink, Debra
Mudimu, Edinah
Stover, John
Bansi-Matharu, Loveleen
Martin-Hughes, Rowan
Wulan, Nisaa
Cambiano, Valentina
Smith, Jennifer
Bershteyn, Anna
Meyer-Rath, Gesine
Jamieson, Lise
Johnson, Leigh F.
author_sort Moolla, Haroon
collection PubMed
description BACKGROUND: Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the robustness of estimates and highlight research gaps. As part of a larger project aiming to determine the optimal allocation of funding for HIV services, in this study we compare projections from five mathematical models of the HIV epidemic in South Africa: EMOD-HIV, Goals, HIV-Synthesis, Optima, and Thembisa. METHODS: The five modelling groups produced estimates of the total population, HIV incidence, HIV prevalence, proportion of people living with HIV who are diagnosed, ART coverage, proportion of those on ART who are virally suppressed, AIDS-related deaths, total deaths, and the proportion of adult males who are circumcised. Estimates were made under a “status quo” scenario for the period 1990 to 2040. For each output variable we assessed the consistency of model estimates by calculating the coefficient of variation and examining the trend over time. RESULTS: For most outputs there was significant inter-model variability between 1990 and 2005, when limited data was available for calibration, good consistency from 2005 to 2025, and increasing variability towards the end of the projection period. Estimates of HIV incidence, deaths in people living with HIV, and total deaths displayed the largest long-term variability, with standard deviations between 35 and 65% of the cross-model means. Despite this variability, all models predicted a gradual decline in HIV incidence in the long-term. Projections related to the UNAIDS 95–95-95 targets were more consistent, with the coefficients of variation below 0.1 for all groups except children. CONCLUSIONS: While models produced consistent estimates for several outputs, there are areas of variability that should be investigated. This is important if projections are to be used in subsequent cost-effectiveness studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-16995-9.
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spelling pubmed-106122952023-10-29 A quantitative assessment of the consistency of projections from five mathematical models of the HIV epidemic in South Africa: a model comparison study Moolla, Haroon Phillips, Andrew ten Brink, Debra Mudimu, Edinah Stover, John Bansi-Matharu, Loveleen Martin-Hughes, Rowan Wulan, Nisaa Cambiano, Valentina Smith, Jennifer Bershteyn, Anna Meyer-Rath, Gesine Jamieson, Lise Johnson, Leigh F. BMC Public Health Research BACKGROUND: Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the robustness of estimates and highlight research gaps. As part of a larger project aiming to determine the optimal allocation of funding for HIV services, in this study we compare projections from five mathematical models of the HIV epidemic in South Africa: EMOD-HIV, Goals, HIV-Synthesis, Optima, and Thembisa. METHODS: The five modelling groups produced estimates of the total population, HIV incidence, HIV prevalence, proportion of people living with HIV who are diagnosed, ART coverage, proportion of those on ART who are virally suppressed, AIDS-related deaths, total deaths, and the proportion of adult males who are circumcised. Estimates were made under a “status quo” scenario for the period 1990 to 2040. For each output variable we assessed the consistency of model estimates by calculating the coefficient of variation and examining the trend over time. RESULTS: For most outputs there was significant inter-model variability between 1990 and 2005, when limited data was available for calibration, good consistency from 2005 to 2025, and increasing variability towards the end of the projection period. Estimates of HIV incidence, deaths in people living with HIV, and total deaths displayed the largest long-term variability, with standard deviations between 35 and 65% of the cross-model means. Despite this variability, all models predicted a gradual decline in HIV incidence in the long-term. Projections related to the UNAIDS 95–95-95 targets were more consistent, with the coefficients of variation below 0.1 for all groups except children. CONCLUSIONS: While models produced consistent estimates for several outputs, there are areas of variability that should be investigated. This is important if projections are to be used in subsequent cost-effectiveness studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-16995-9. BioMed Central 2023-10-27 /pmc/articles/PMC10612295/ /pubmed/37891514 http://dx.doi.org/10.1186/s12889-023-16995-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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
Moolla, Haroon
Phillips, Andrew
ten Brink, Debra
Mudimu, Edinah
Stover, John
Bansi-Matharu, Loveleen
Martin-Hughes, Rowan
Wulan, Nisaa
Cambiano, Valentina
Smith, Jennifer
Bershteyn, Anna
Meyer-Rath, Gesine
Jamieson, Lise
Johnson, Leigh F.
A quantitative assessment of the consistency of projections from five mathematical models of the HIV epidemic in South Africa: a model comparison study
title A quantitative assessment of the consistency of projections from five mathematical models of the HIV epidemic in South Africa: a model comparison study
title_full A quantitative assessment of the consistency of projections from five mathematical models of the HIV epidemic in South Africa: a model comparison study
title_fullStr A quantitative assessment of the consistency of projections from five mathematical models of the HIV epidemic in South Africa: a model comparison study
title_full_unstemmed A quantitative assessment of the consistency of projections from five mathematical models of the HIV epidemic in South Africa: a model comparison study
title_short A quantitative assessment of the consistency of projections from five mathematical models of the HIV epidemic in South Africa: a model comparison study
title_sort quantitative assessment of the consistency of projections from five mathematical models of the hiv epidemic in south africa: a model comparison study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612295/
https://www.ncbi.nlm.nih.gov/pubmed/37891514
http://dx.doi.org/10.1186/s12889-023-16995-9
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