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TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions

Tuberculosis (TB) is the leading cause of death from infectious disease worldwide, predominantly affecting low- and middle-income countries (LMICs), where resources are limited. As such, countries need to be able to choose the most efficient interventions for their respective setting. Mathematical m...

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Autores principales: Houben, R. M. G. J., Lalli, M., Sumner, T., Hamilton, M., Pedrazzoli, D., Bonsu, F., Hippner, P., Pillay, Y., Kimerling, M., Ahmedov, S., Pretorius, C., White, R. G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4806495/
https://www.ncbi.nlm.nih.gov/pubmed/27012808
http://dx.doi.org/10.1186/s12916-016-0608-4
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author Houben, R. M. G. J.
Lalli, M.
Sumner, T.
Hamilton, M.
Pedrazzoli, D.
Bonsu, F.
Hippner, P.
Pillay, Y.
Kimerling, M.
Ahmedov, S.
Pretorius, C.
White, R. G.
author_facet Houben, R. M. G. J.
Lalli, M.
Sumner, T.
Hamilton, M.
Pedrazzoli, D.
Bonsu, F.
Hippner, P.
Pillay, Y.
Kimerling, M.
Ahmedov, S.
Pretorius, C.
White, R. G.
author_sort Houben, R. M. G. J.
collection PubMed
description Tuberculosis (TB) is the leading cause of death from infectious disease worldwide, predominantly affecting low- and middle-income countries (LMICs), where resources are limited. As such, countries need to be able to choose the most efficient interventions for their respective setting. Mathematical models can be valuable tools to inform rational policy decisions and improve resource allocation, but are often unavailable or inaccessible for LMICs, particularly in TB. We developed TIME Impact, a user-friendly TB model that enables local capacity building and strengthens country-specific policy discussions to inform support funding applications at the (sub-)national level (e.g. Ministry of Finance) or to international donors (e.g. the Global Fund to Fight AIDS, Tuberculosis and Malaria). TIME Impact is an epidemiological transmission model nested in TIME, a set of TB modelling tools available for free download within the widely-used Spectrum software. The TIME Impact model reflects key aspects of the natural history of TB, with additional structure for HIV/ART, drug resistance, treatment history and age. TIME Impact enables national TB programmes (NTPs) and other TB policymakers to better understand their own TB epidemic, plan their response, apply for funding and evaluate the implementation of the response. The explicit aim of TIME Impact’s user-friendly interface is to enable training of local and international TB experts towards independent use. During application of TIME Impact, close involvement of the NTPs and other local partners also builds critical understanding of the modelling methods, assumptions and limitations inherent to modelling. This is essential to generate broad country-level ownership of the modelling data inputs and results. In turn, it stimulates discussions and a review of the current evidence and assumptions, strengthening the decision-making process in general. TIME Impact has been effectively applied in a variety of settings. In South Africa, it informed the first South African HIV and TB Investment Cases and successfully leveraged additional resources from the National Treasury at a time of austerity. In Ghana, a long-term TIME model-centred interaction with the NTP provided new insights into the local epidemiology and guided resource allocation decisions to improve impact. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12916-016-0608-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-48064952016-03-25 TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions Houben, R. M. G. J. Lalli, M. Sumner, T. Hamilton, M. Pedrazzoli, D. Bonsu, F. Hippner, P. Pillay, Y. Kimerling, M. Ahmedov, S. Pretorius, C. White, R. G. BMC Med Correspondence Tuberculosis (TB) is the leading cause of death from infectious disease worldwide, predominantly affecting low- and middle-income countries (LMICs), where resources are limited. As such, countries need to be able to choose the most efficient interventions for their respective setting. Mathematical models can be valuable tools to inform rational policy decisions and improve resource allocation, but are often unavailable or inaccessible for LMICs, particularly in TB. We developed TIME Impact, a user-friendly TB model that enables local capacity building and strengthens country-specific policy discussions to inform support funding applications at the (sub-)national level (e.g. Ministry of Finance) or to international donors (e.g. the Global Fund to Fight AIDS, Tuberculosis and Malaria). TIME Impact is an epidemiological transmission model nested in TIME, a set of TB modelling tools available for free download within the widely-used Spectrum software. The TIME Impact model reflects key aspects of the natural history of TB, with additional structure for HIV/ART, drug resistance, treatment history and age. TIME Impact enables national TB programmes (NTPs) and other TB policymakers to better understand their own TB epidemic, plan their response, apply for funding and evaluate the implementation of the response. The explicit aim of TIME Impact’s user-friendly interface is to enable training of local and international TB experts towards independent use. During application of TIME Impact, close involvement of the NTPs and other local partners also builds critical understanding of the modelling methods, assumptions and limitations inherent to modelling. This is essential to generate broad country-level ownership of the modelling data inputs and results. In turn, it stimulates discussions and a review of the current evidence and assumptions, strengthening the decision-making process in general. TIME Impact has been effectively applied in a variety of settings. In South Africa, it informed the first South African HIV and TB Investment Cases and successfully leveraged additional resources from the National Treasury at a time of austerity. In Ghana, a long-term TIME model-centred interaction with the NTP provided new insights into the local epidemiology and guided resource allocation decisions to improve impact. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12916-016-0608-4) contains supplementary material, which is available to authorized users. BioMed Central 2016-03-24 /pmc/articles/PMC4806495/ /pubmed/27012808 http://dx.doi.org/10.1186/s12916-016-0608-4 Text en © Houben et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Correspondence
Houben, R. M. G. J.
Lalli, M.
Sumner, T.
Hamilton, M.
Pedrazzoli, D.
Bonsu, F.
Hippner, P.
Pillay, Y.
Kimerling, M.
Ahmedov, S.
Pretorius, C.
White, R. G.
TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions
title TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions
title_full TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions
title_fullStr TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions
title_full_unstemmed TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions
title_short TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions
title_sort time impact – a new user-friendly tuberculosis (tb) model to inform tb policy decisions
topic Correspondence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4806495/
https://www.ncbi.nlm.nih.gov/pubmed/27012808
http://dx.doi.org/10.1186/s12916-016-0608-4
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