TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions
Identifieur interne : 000063 ( Pmc/Curation ); précédent : 000062; suivant : 000064TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions
Auteurs : R. M. G. J. Houben [Royaume-Uni] ; M. Lalli [Royaume-Uni] ; T. Sumner [Royaume-Uni] ; M. Hamilton [États-Unis] ; D. Pedrazzoli [Royaume-Uni] ; F. Bonsu [Ghana] ; P. Hippner [Afrique du Sud] ; Y. Pillay [Afrique du Sud] ; M. Kimerling [Pays-Bas] ; S. Ahmedov [États-Unis] ; C. Pretorius [États-Unis] ; R. G. White [Royaume-Uni]Source :
- BMC Medicine [ 1741-7015 ] ; 2016.
Abstract
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.
The online version of this article (doi:10.1186/s12916-016-0608-4) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1186/s12916-016-0608-4
PubMed: 27012808
PubMed Central: 4806495
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Ahmedov</name><affiliation wicri:level="2"><nlm:aff id="Aff8">USAID, Washington, DC USA</nlm:aff><country>États-Unis</country><placeName><region type="state">District de Columbia</region></placeName><wicri:cityArea>USAID, Washington</wicri:cityArea></affiliation></author><author><name sortKey="Pretorius, C" sort="Pretorius, C" uniqKey="Pretorius C" first="C." last="Pretorius">C. Pretorius</name><affiliation wicri:level="2"><nlm:aff id="Aff3">Avenir Health, Glastonbury, CT USA</nlm:aff><country>États-Unis</country><placeName><region type="state">Connecticut</region></placeName><wicri:cityArea>Avenir Health, Glastonbury</wicri:cityArea></affiliation></author><author><name sortKey="White, R G" sort="White, R G" uniqKey="White R" first="R. G." last="White">R. G. White</name><affiliation wicri:level="1"><nlm:aff id="Aff1">TB Modelling Group, TB Centre, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK</nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>TB Modelling Group, TB Centre, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="Aff2">Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK</nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London</wicri:regionArea></affiliation></author></analytic><series><title level="j">BMC Medicine</title><idno type="eISSN">1741-7015</idno><imprint><date when="2016">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>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).</p><p>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.</p><p>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.</p><p>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.</p><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1186/s12916-016-0608-4) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Lonnroth, K" uniqKey="Lonnroth K">K Lonnroth</name></author><author><name sortKey="Glaziou, P" uniqKey="Glaziou P">P Glaziou</name></author><author><name sortKey="Weil, D" uniqKey="Weil D">D Weil</name></author><author><name sortKey="Floyd, K" uniqKey="Floyd K">K Floyd</name></author><author><name sortKey="Uplekar, M" uniqKey="Uplekar M">M Uplekar</name></author><author><name sortKey="Raviglione, M" uniqKey="Raviglione M">M 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<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Med</journal-id><journal-id journal-id-type="iso-abbrev">BMC Med</journal-id><journal-title-group><journal-title>BMC Medicine</journal-title></journal-title-group><issn pub-type="epub">1741-7015</issn><publisher><publisher-name>BioMed Central</publisher-name><publisher-loc>London</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">27012808</article-id><article-id pub-id-type="pmc">4806495</article-id><article-id pub-id-type="publisher-id">608</article-id><article-id pub-id-type="doi">10.1186/s12916-016-0608-4</article-id><article-categories><subj-group subj-group-type="heading"><subject>Correspondence</subject></subj-group></article-categories><title-group><article-title>TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name><surname>Houben</surname><given-names>R. M. G. J.</given-names></name><address><phone>+44 20 7927 2956</phone><email>rein.houben@lshtm.ac.uk</email></address><xref ref-type="aff" rid="Aff1"></xref><xref ref-type="aff" rid="Aff2"></xref></contrib><contrib contrib-type="author"><name><surname>Lalli</surname><given-names>M.</given-names></name><xref ref-type="aff" rid="Aff1"></xref><xref ref-type="aff" rid="Aff2"></xref></contrib><contrib contrib-type="author"><name><surname>Sumner</surname><given-names>T.</given-names></name><xref ref-type="aff" rid="Aff1"></xref><xref ref-type="aff" rid="Aff2"></xref></contrib><contrib contrib-type="author"><name><surname>Hamilton</surname><given-names>M.</given-names></name><xref ref-type="aff" rid="Aff3"></xref></contrib><contrib contrib-type="author"><name><surname>Pedrazzoli</surname><given-names>D.</given-names></name><xref ref-type="aff" rid="Aff1"></xref><xref ref-type="aff" rid="Aff2"></xref></contrib><contrib contrib-type="author"><name><surname>Bonsu</surname><given-names>F.</given-names></name><xref ref-type="aff" rid="Aff4"></xref></contrib><contrib contrib-type="author"><name><surname>Hippner</surname><given-names>P.</given-names></name><xref ref-type="aff" rid="Aff5"></xref></contrib><contrib contrib-type="author"><name><surname>Pillay</surname><given-names>Y.</given-names></name><xref ref-type="aff" rid="Aff6"></xref></contrib><contrib contrib-type="author"><name><surname>Kimerling</surname><given-names>M.</given-names></name><xref ref-type="aff" rid="Aff7"></xref></contrib><contrib contrib-type="author"><name><surname>Ahmedov</surname><given-names>S.</given-names></name><xref ref-type="aff" rid="Aff8"></xref></contrib><contrib contrib-type="author"><name><surname>Pretorius</surname><given-names>C.</given-names></name><xref ref-type="aff" rid="Aff3"></xref></contrib><contrib contrib-type="author"><name><surname>White</surname><given-names>R. G.</given-names></name><xref ref-type="aff" rid="Aff1"></xref><xref ref-type="aff" rid="Aff2"></xref></contrib><aff id="Aff1"><label></label>TB Modelling Group, TB Centre, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK</aff><aff id="Aff2"><label></label>Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK</aff><aff id="Aff3"><label></label>Avenir Health, Glastonbury, CT USA</aff><aff id="Aff4"><label></label>National Tuberculosis Control Programme, Ghana Health Service, Accra, Ghana</aff><aff id="Aff5"><label></label>Aurum Institute, Johannesburg, South Africa</aff><aff id="Aff6"><label></label>National Department of Health, Pretoria, South Africa</aff><aff id="Aff7"><label></label>KNCV Tuberculosis Foundation, The Hague, The Netherlands</aff><aff id="Aff8"><label></label>USAID, Washington, DC USA</aff></contrib-group><pub-date pub-type="epub"><day>24</day><month>3</month><year>2016</year></pub-date><pub-date pub-type="pmc-release"><day>24</day><month>3</month><year>2016</year></pub-date><pub-date pub-type="collection"><year>2016</year></pub-date><volume>14</volume><elocation-id>56</elocation-id><history><date date-type="received"><day>16</day><month>1</month><year>2016</year></date><date date-type="accepted"><day>22</day><month>3</month><year>2016</year></date></history><permissions><copyright-statement>© Houben et al. 2016</copyright-statement><license license-type="OpenAccess"><license-p><bold>Open Access</bold>This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>), 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 (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>) applies to the data made available in this article, unless otherwise stated.</license-p></license></permissions><abstract id="Abs1"><p>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).</p><p>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.</p><p>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.</p><p>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.</p><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1186/s12916-016-0608-4) contains supplementary material, which is available to authorized users.</p></sec></abstract><kwd-group xml:lang="en"><title>Keywords</title><kwd>Capacity building</kwd><kwd>Mathematical modelling</kwd><kwd>Policy support</kwd><kwd>Tuberculosis</kwd></kwd-group><funding-group><award-group><funding-source><institution>United States Agency for International Development (US)</institution></funding-source><award-id>GHN-A-00-08-00004-00</award-id></award-group></funding-group><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© The Author(s) 2016</meta-value></custom-meta></custom-meta-group></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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