Optima TB: A tool to help optimally allocate tuberculosis spending.
Approximately 85% of tuberculosis (TB) related deaths occur in low- and middle-income countries where health resources are scarce. Effective priority setting is required to maximise the impact of limited budgets. The Optima TB tool has been developed to support analytical capacity and inform evidenc...
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Public Library of Science (PLoS)
2021
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oai:doaj.org-article:c95089104a5f4a9790e3681c03e3e3032021-12-02T19:58:13ZOptima TB: A tool to help optimally allocate tuberculosis spending.1553-734X1553-735810.1371/journal.pcbi.1009255https://doaj.org/article/c95089104a5f4a9790e3681c03e3e3032021-09-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009255https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Approximately 85% of tuberculosis (TB) related deaths occur in low- and middle-income countries where health resources are scarce. Effective priority setting is required to maximise the impact of limited budgets. The Optima TB tool has been developed to support analytical capacity and inform evidence-based priority setting processes for TB health benefits package design. This paper outlines the Optima TB framework and how it was applied in Belarus, an upper-middle income country in Eastern Europe with a relatively high burden of TB. Optima TB is a population-based disease transmission model, with programmatic cost functions and an optimisation algorithm. Modelled populations include age-differentiated general populations and higher-risk populations such as people living with HIV. Populations and prospective interventions are defined in consultation with local stakeholders. In partnership with the latter, demographic, epidemiological, programmatic, as well as cost and spending data for these populations and interventions are then collated. An optimisation analysis of TB spending was conducted in Belarus, using program objectives and constraints defined in collaboration with local stakeholders, which included experts, decision makers, funders and organisations involved in service delivery, support and technical assistance. These analyses show that it is possible to improve health impact by redistributing current TB spending in Belarus. Specifically, shifting funding from inpatient- to outpatient-focused care models, and from mass screening to active case finding strategies, could reduce TB prevalence and mortality by up to 45% and 50%, respectively, by 2035. In addition, an optimised allocation of TB spending could lead to a reduction in drug-resistant TB infections by 40% over this period. This would support progress towards national TB targets without additional financial resources. The case study in Belarus demonstrates how reallocations of spending across existing and new interventions could have a substantial impact on TB outcomes. This highlights the potential for Optima TB and similar modelling tools to support evidence-based priority setting.Lara GoscéGerard J Abou JaoudeDavid J KedzioraClemens BenediktAzfar HussainSarah JarvisAlena SkrahinaDzmitry KlimukHenadz HurevichFeng ZhaoNicole Fraser-HurtNejma CheikhMarelize GorgensDavid J WilsonRomesh AbeysuriyaRowan Martin-HughesSherrie L KellyAnna RobertsRobyn M StuartTom PalmerJasmina Panovska-GriffithsCliff C KerrDavid P WilsonHassan Haghparast-BidgoliJolene SkordisIbrahim AbubakarPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 9, p e1009255 (2021) |
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Biology (General) QH301-705.5 |
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Biology (General) QH301-705.5 Lara Goscé Gerard J Abou Jaoude David J Kedziora Clemens Benedikt Azfar Hussain Sarah Jarvis Alena Skrahina Dzmitry Klimuk Henadz Hurevich Feng Zhao Nicole Fraser-Hurt Nejma Cheikh Marelize Gorgens David J Wilson Romesh Abeysuriya Rowan Martin-Hughes Sherrie L Kelly Anna Roberts Robyn M Stuart Tom Palmer Jasmina Panovska-Griffiths Cliff C Kerr David P Wilson Hassan Haghparast-Bidgoli Jolene Skordis Ibrahim Abubakar Optima TB: A tool to help optimally allocate tuberculosis spending. |
| description |
Approximately 85% of tuberculosis (TB) related deaths occur in low- and middle-income countries where health resources are scarce. Effective priority setting is required to maximise the impact of limited budgets. The Optima TB tool has been developed to support analytical capacity and inform evidence-based priority setting processes for TB health benefits package design. This paper outlines the Optima TB framework and how it was applied in Belarus, an upper-middle income country in Eastern Europe with a relatively high burden of TB. Optima TB is a population-based disease transmission model, with programmatic cost functions and an optimisation algorithm. Modelled populations include age-differentiated general populations and higher-risk populations such as people living with HIV. Populations and prospective interventions are defined in consultation with local stakeholders. In partnership with the latter, demographic, epidemiological, programmatic, as well as cost and spending data for these populations and interventions are then collated. An optimisation analysis of TB spending was conducted in Belarus, using program objectives and constraints defined in collaboration with local stakeholders, which included experts, decision makers, funders and organisations involved in service delivery, support and technical assistance. These analyses show that it is possible to improve health impact by redistributing current TB spending in Belarus. Specifically, shifting funding from inpatient- to outpatient-focused care models, and from mass screening to active case finding strategies, could reduce TB prevalence and mortality by up to 45% and 50%, respectively, by 2035. In addition, an optimised allocation of TB spending could lead to a reduction in drug-resistant TB infections by 40% over this period. This would support progress towards national TB targets without additional financial resources. The case study in Belarus demonstrates how reallocations of spending across existing and new interventions could have a substantial impact on TB outcomes. This highlights the potential for Optima TB and similar modelling tools to support evidence-based priority setting. |
| format |
article |
| author |
Lara Goscé Gerard J Abou Jaoude David J Kedziora Clemens Benedikt Azfar Hussain Sarah Jarvis Alena Skrahina Dzmitry Klimuk Henadz Hurevich Feng Zhao Nicole Fraser-Hurt Nejma Cheikh Marelize Gorgens David J Wilson Romesh Abeysuriya Rowan Martin-Hughes Sherrie L Kelly Anna Roberts Robyn M Stuart Tom Palmer Jasmina Panovska-Griffiths Cliff C Kerr David P Wilson Hassan Haghparast-Bidgoli Jolene Skordis Ibrahim Abubakar |
| author_facet |
Lara Goscé Gerard J Abou Jaoude David J Kedziora Clemens Benedikt Azfar Hussain Sarah Jarvis Alena Skrahina Dzmitry Klimuk Henadz Hurevich Feng Zhao Nicole Fraser-Hurt Nejma Cheikh Marelize Gorgens David J Wilson Romesh Abeysuriya Rowan Martin-Hughes Sherrie L Kelly Anna Roberts Robyn M Stuart Tom Palmer Jasmina Panovska-Griffiths Cliff C Kerr David P Wilson Hassan Haghparast-Bidgoli Jolene Skordis Ibrahim Abubakar |
| author_sort |
Lara Goscé |
| title |
Optima TB: A tool to help optimally allocate tuberculosis spending. |
| title_short |
Optima TB: A tool to help optimally allocate tuberculosis spending. |
| title_full |
Optima TB: A tool to help optimally allocate tuberculosis spending. |
| title_fullStr |
Optima TB: A tool to help optimally allocate tuberculosis spending. |
| title_full_unstemmed |
Optima TB: A tool to help optimally allocate tuberculosis spending. |
| title_sort |
optima tb: a tool to help optimally allocate tuberculosis spending. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2021 |
| url |
https://doaj.org/article/c95089104a5f4a9790e3681c03e3e303 |
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