TY - JOUR

T1 - Optima TB

T2 - A tool to help optimally allocate tuberculosis spending

AU - Goscé, Lara

AU - Abou Jaoude, Gerard J.

AU - Kedziora, David J.

AU - Benedikt, Clemens

AU - Hussain, Azfar

AU - Jarvis, Sarah

AU - Skrahina, Alena

AU - Klimuk, Dzmitry

AU - Hurevich, Henadz

AU - Zhao, Feng

AU - Fraser-Hurt, Nicole

AU - Cheikh, Nejma

AU - Gorgens, Marelize

AU - Wilson, David J.

AU - Abeysuriya, Romesh

AU - Martin-Hughes, Rowan

AU - Kelly, Sherrie L.

AU - Roberts, Anna

AU - Stuart, Robyn M.

AU - Palmer, Tom

AU - Panovska-Griffiths, Jasmina

AU - Kerr, Cliff C.

AU - Wilson, David P.

AU - Haghparast-Bidgoli, Hassan

AU - Skordis, Jolene

AU - Abubakar, Ibrahim

N1 - Publisher Copyright: © 2021 Goscé et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

U2 - 10.1371/JOURNAL.PCBI.1009255

DO - 10.1371/JOURNAL.PCBI.1009255

M3 - Journal article

C2 - 34570767

AN - SCOPUS:85118097024

VL - 17

JO - P L o S Computational Biology (Online)

JF - P L o S Computational Biology (Online)

SN - 1553-734X

IS - 9

M1 - e1009255

ER -