PopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial.

Mathematical models are powerful tools in HIV epidemiology, producing quantitative projections of key indicators such as HIV incidence and prevalence. In order to improve the accuracy of predictions, such models need to incorporate a number of behavioural and biological heterogeneities, especially t...

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Autores principales:	Michael Pickles, Anne Cori, William J M Probert, Rafael Sauter, Robert Hinch, Sarah Fidler, Helen Ayles, Peter Bock, Deborah Donnell, Ethan Wilson, Estelle Piwowar-Manning, Sian Floyd, Richard J Hayes, Christophe Fraser, HPTN 071 (PopART) Study Team
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/affef60ff94443cda079aebd0c49e70c
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spelling	oai:doaj.org-article:affef60ff94443cda079aebd0c49e70c2021-12-02T19:57:52ZPopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial.1553-734X1553-735810.1371/journal.pcbi.1009301https://doaj.org/article/affef60ff94443cda079aebd0c49e70c2021-09-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009301https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Mathematical models are powerful tools in HIV epidemiology, producing quantitative projections of key indicators such as HIV incidence and prevalence. In order to improve the accuracy of predictions, such models need to incorporate a number of behavioural and biological heterogeneities, especially those related to the sexual network within which HIV transmission occurs. An individual-based model, which explicitly models sexual partnerships, is thus often the most natural type of model to choose. In this paper we present PopART-IBM, a computationally efficient individual-based model capable of simulating 50 years of an HIV epidemic in a large, high-prevalence community in under a minute. We show how the model calibrates within a Bayesian inference framework to detailed age- and sex-stratified data from multiple sources on HIV prevalence, awareness of HIV status, ART status, and viral suppression for an HPTN 071 (PopART) study community in Zambia, and present future projections of HIV prevalence and incidence for this community in the absence of trial intervention.Michael PicklesAnne CoriWilliam J M ProbertRafael SauterRobert HinchSarah FidlerHelen AylesPeter BockDeborah DonnellEthan WilsonEstelle Piwowar-ManningSian FloydRichard J HayesChristophe FraserHPTN 071 (PopART) Study TeamPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 9, p e1009301 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Michael Pickles Anne Cori William J M Probert Rafael Sauter Robert Hinch Sarah Fidler Helen Ayles Peter Bock Deborah Donnell Ethan Wilson Estelle Piwowar-Manning Sian Floyd Richard J Hayes Christophe Fraser HPTN 071 (PopART) Study Team PopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial.
description	Mathematical models are powerful tools in HIV epidemiology, producing quantitative projections of key indicators such as HIV incidence and prevalence. In order to improve the accuracy of predictions, such models need to incorporate a number of behavioural and biological heterogeneities, especially those related to the sexual network within which HIV transmission occurs. An individual-based model, which explicitly models sexual partnerships, is thus often the most natural type of model to choose. In this paper we present PopART-IBM, a computationally efficient individual-based model capable of simulating 50 years of an HIV epidemic in a large, high-prevalence community in under a minute. We show how the model calibrates within a Bayesian inference framework to detailed age- and sex-stratified data from multiple sources on HIV prevalence, awareness of HIV status, ART status, and viral suppression for an HPTN 071 (PopART) study community in Zambia, and present future projections of HIV prevalence and incidence for this community in the absence of trial intervention.
format	article
author	Michael Pickles Anne Cori William J M Probert Rafael Sauter Robert Hinch Sarah Fidler Helen Ayles Peter Bock Deborah Donnell Ethan Wilson Estelle Piwowar-Manning Sian Floyd Richard J Hayes Christophe Fraser HPTN 071 (PopART) Study Team
author_facet	Michael Pickles Anne Cori William J M Probert Rafael Sauter Robert Hinch Sarah Fidler Helen Ayles Peter Bock Deborah Donnell Ethan Wilson Estelle Piwowar-Manning Sian Floyd Richard J Hayes Christophe Fraser HPTN 071 (PopART) Study Team
author_sort	Michael Pickles
title	PopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial.
title_short	PopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial.
title_full	PopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial.
title_fullStr	PopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial.
title_full_unstemmed	PopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial.
title_sort	popart-ibm, a highly efficient stochastic individual-based simulation model of generalised hiv epidemics developed in the context of the hptn 071 (popart) trial.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/affef60ff94443cda079aebd0c49e70c
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PopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial.

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