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Optima TB: A tool to help optimally allocate tuberculosis spending
- Source :
- PLoS Computational Biology, PLoS Computational Biology, Vol 17, Iss 9, p e1009255 (2021), Goscé, L, Abou Jaoude, G J, Kedziora, D J, Benedikt, C, Hussain, A, Jarvis, S, Skrahina, A, Klimuk, D, Hurevich, H, Zhao, F, Fraser-Hurt, N, Cheikh, N, Gorgens, M, Wilson, D J, Abeysuriya, R, Martin-Hughes, R, Kelly, S L, Roberts, A, Stuart, R M, Palmer, T, Panovska-Griffiths, J, Kerr, C C, Wilson, D P, Haghparast-Bidgoli, H, Skordis, J & Abubakar, I 2021, ' Optima TB : A tool to help optimally allocate tuberculosis spending ', PLOS Computational Biology, vol. 17, no. 9, e1009255 . https://doi.org/10.1371/JOURNAL.PCBI.1009255
- Publication Year :
- 2021
- Publisher :
- Public Library of Science (PLoS), 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 />Author summary Tuberculosis (TB) remains a leading global cause of death and morbidity, and 85% of deaths occur in countries where resources for TB care and control are limited. Many countries cannot finance all TB interventions or technologies, which means difficult decisions on what to prioritise and publically finance. Modelling tools can help decision-makers set priorities based on evidence, in a systematic and transparent way. This study presents Optima TB, a tool that estimates which allocations of spending across interventions will most likely maximise specified objectives—such as minimising TB deaths, prevalence and incidence. In partnership with local decision-makers and stakeholders, Optima TB was applied in Belarus. Recommendations from the model findings include focussing investment on outpatient rather than inpatient care and actively finding people with TB (e.g. through contact tracing) rather than mass testing of the population. The recommended reallocations of spending could reduce TB prevalence and deaths by up to 45% and 50%, respectively, by 2035 for the same amount of spending. Key stakeholders were engaged throughout the analysis and findings and uncertainty around the results were clearly communicated with decision-makers. The timeliness of the results helped inform national dialogue on TB care reform, among other key policy discussions.
- Subjects :
- Bacterial Diseases
Male
Republic of Belarus
Epidemiology
Economics
Service delivery framework
Extensively Drug-Resistant Tuberculosis
Cost-Benefit Analysis
Psychological intervention
Social Sciences
Geographical Locations
Medical Conditions
Medicine and Health Sciences
Prevalence
Prospective Studies
Biology (General)
Child
Aged, 80 and over
education.field_of_study
Ecology
Pharmaceutics
Multi-Drug-Resistant Tuberculosis
Belarus
Health Care Costs
Middle Aged
Europe
Infectious Diseases
Models, Economic
Computational Theory and Mathematics
Child, Preschool
Modeling and Simulation
General partnership
Physical Sciences
Female
01 Mathematical Sciences, 06 Biological Sciences, 08 Information and Computing Sciences
Algorithms
Research Article
Optimization
Adult
medicine.medical_specialty
Tuberculosis
Adolescent
QH301-705.5
Bioinformatics
Population
Models, Biological
Resource Allocation
Young Adult
Cellular and Molecular Neuroscience
Drug Therapy
Environmental health
Genetics
medicine
Income country
Humans
education
Molecular Biology
Ecology, Evolution, Behavior and Systematics
Mass screening
Aged
Infant, Newborn
Computational Biology
Infant
Tropical Diseases
medicine.disease
People and Places
Business
Mathematics
Finance
Software
Subjects
Details
- ISSN :
- 15537358
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- PLOS Computational Biology
- Accession number :
- edsair.doi.dedup.....264d602aaeae45ea12f344cebad228eb