Cargando…
Modelling the epidemiologic impact of achieving UNAIDS fast-track 90-90-90 and 95-95-95 targets in South Africa
UNAIDS established fast-track targets of 73% and 86% viral suppression among human immunodeficiency virus (HIV)-positive individuals by 2020 and 2030, respectively. The epidemiologic impact of achieving these goals is unknown. The HIV-Calibrated Dynamic Model, a calibrated agent-based model of HIV t...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6452860/ https://www.ncbi.nlm.nih.gov/pubmed/30869008 http://dx.doi.org/10.1017/S0950268818003497 |
_version_ | 1783409356684918784 |
---|---|
author | Abuelezam, N. N. McCormick, A. W. Surface, E. D. Fussell, T. Freedberg, K. A. Lipsitch, M. Seage, G. R. |
author_facet | Abuelezam, N. N. McCormick, A. W. Surface, E. D. Fussell, T. Freedberg, K. A. Lipsitch, M. Seage, G. R. |
author_sort | Abuelezam, N. N. |
collection | PubMed |
description | UNAIDS established fast-track targets of 73% and 86% viral suppression among human immunodeficiency virus (HIV)-positive individuals by 2020 and 2030, respectively. The epidemiologic impact of achieving these goals is unknown. The HIV-Calibrated Dynamic Model, a calibrated agent-based model of HIV transmission, is used to examine scenarios of incremental improvements to the testing and antiretroviral therapy (ART) continuum in South Africa in 2015. The speed of intervention availability is explored, comparing policies for their predicted effects on incidence, prevalence and achievement of fast-track targets in 2020 and 2030. Moderate (30%) improvements in the continuum will not achieve 2020 or 2030 targets and have modest impacts on incidence and prevalence. Improving the continuum by 80% and increasing availability reduces incidence from 2.54 to 0.80 per 100 person-years (−1.73, interquartile range (IQR): −1.42, −2.13) and prevalence from 26.0 to 24.6% (−1.4 percentage points, IQR: −0.88, −1.92) from 2015 to 2030 and achieves fast track targets in 2020 and 2030. Achieving 90-90-90 in South Africa is possible with large improvements to the testing and treatment continuum. The epidemiologic impact of these improvements depends on the balance between survival and transmission benefits of ART with the potential for incidence to remain high. |
format | Online Article Text |
id | pubmed-6452860 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-64528602019-04-08 Modelling the epidemiologic impact of achieving UNAIDS fast-track 90-90-90 and 95-95-95 targets in South Africa Abuelezam, N. N. McCormick, A. W. Surface, E. D. Fussell, T. Freedberg, K. A. Lipsitch, M. Seage, G. R. Epidemiol Infect Original Paper UNAIDS established fast-track targets of 73% and 86% viral suppression among human immunodeficiency virus (HIV)-positive individuals by 2020 and 2030, respectively. The epidemiologic impact of achieving these goals is unknown. The HIV-Calibrated Dynamic Model, a calibrated agent-based model of HIV transmission, is used to examine scenarios of incremental improvements to the testing and antiretroviral therapy (ART) continuum in South Africa in 2015. The speed of intervention availability is explored, comparing policies for their predicted effects on incidence, prevalence and achievement of fast-track targets in 2020 and 2030. Moderate (30%) improvements in the continuum will not achieve 2020 or 2030 targets and have modest impacts on incidence and prevalence. Improving the continuum by 80% and increasing availability reduces incidence from 2.54 to 0.80 per 100 person-years (−1.73, interquartile range (IQR): −1.42, −2.13) and prevalence from 26.0 to 24.6% (−1.4 percentage points, IQR: −0.88, −1.92) from 2015 to 2030 and achieves fast track targets in 2020 and 2030. Achieving 90-90-90 in South Africa is possible with large improvements to the testing and treatment continuum. The epidemiologic impact of these improvements depends on the balance between survival and transmission benefits of ART with the potential for incidence to remain high. Cambridge University Press 2019-03-01 /pmc/articles/PMC6452860/ /pubmed/30869008 http://dx.doi.org/10.1017/S0950268818003497 Text en © The Author(s) 2019 http://creativecommons.org/licenses/by/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Paper Abuelezam, N. N. McCormick, A. W. Surface, E. D. Fussell, T. Freedberg, K. A. Lipsitch, M. Seage, G. R. Modelling the epidemiologic impact of achieving UNAIDS fast-track 90-90-90 and 95-95-95 targets in South Africa |
title | Modelling the epidemiologic impact of achieving UNAIDS fast-track 90-90-90 and 95-95-95 targets in South Africa |
title_full | Modelling the epidemiologic impact of achieving UNAIDS fast-track 90-90-90 and 95-95-95 targets in South Africa |
title_fullStr | Modelling the epidemiologic impact of achieving UNAIDS fast-track 90-90-90 and 95-95-95 targets in South Africa |
title_full_unstemmed | Modelling the epidemiologic impact of achieving UNAIDS fast-track 90-90-90 and 95-95-95 targets in South Africa |
title_short | Modelling the epidemiologic impact of achieving UNAIDS fast-track 90-90-90 and 95-95-95 targets in South Africa |
title_sort | modelling the epidemiologic impact of achieving unaids fast-track 90-90-90 and 95-95-95 targets in south africa |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6452860/ https://www.ncbi.nlm.nih.gov/pubmed/30869008 http://dx.doi.org/10.1017/S0950268818003497 |
work_keys_str_mv | AT abuelezamnn modellingtheepidemiologicimpactofachievingunaidsfasttrack909090and959595targetsinsouthafrica AT mccormickaw modellingtheepidemiologicimpactofachievingunaidsfasttrack909090and959595targetsinsouthafrica AT surfaceed modellingtheepidemiologicimpactofachievingunaidsfasttrack909090and959595targetsinsouthafrica AT fussellt modellingtheepidemiologicimpactofachievingunaidsfasttrack909090and959595targetsinsouthafrica AT freedbergka modellingtheepidemiologicimpactofachievingunaidsfasttrack909090and959595targetsinsouthafrica AT lipsitchm modellingtheepidemiologicimpactofachievingunaidsfasttrack909090and959595targetsinsouthafrica AT seagegr modellingtheepidemiologicimpactofachievingunaidsfasttrack909090and959595targetsinsouthafrica |