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Optima TB: A tool to help optimally allocate tuberculosis spending.
- Source :
-
PLoS computational biology [PLoS Comput Biol] 2021 Sep 27; Vol. 17 (9), pp. e1009255. Date of Electronic Publication: 2021 Sep 27 (Print Publication: 2021). - Publication Year :
- 2021
-
Abstract
- 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.<br />Competing Interests: The authors have declared that no competing interests exist. Author Feng Zhao was unavailable to confirm their authorship contributions. On their behalf, the corresponding author has reported their contributions to the best of their knowledge.
- Subjects :
- Adolescent
Adult
Aged
Aged, 80 and over
Algorithms
Child
Child, Preschool
Computational Biology
Cost-Benefit Analysis
Female
Health Care Costs statistics & numerical data
Humans
Infant
Infant, Newborn
Male
Middle Aged
Models, Biological
Models, Economic
Prevalence
Prospective Studies
Republic of Belarus epidemiology
Tuberculosis epidemiology
Tuberculosis transmission
Young Adult
Resource Allocation economics
Software
Tuberculosis economics
Subjects
Details
- Language :
- English
- ISSN :
- 1553-7358
- Volume :
- 17
- Issue :
- 9
- Database :
- MEDLINE
- Journal :
- PLoS computational biology
- Publication Type :
- Academic Journal
- Accession number :
- 34570767
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1009255