University College London, London, United Kingdom.
Burnet Institute, Melbourne, Australia.
PLoS Comput Biol. 2021 Sep 27;17(9):e1009255. doi: 10.1371/journal.pcbi.1009255. eCollection 2021 Sep.
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.
大约 85%的结核病（TB）相关死亡发生在卫生资源匮乏的中低收入国家。为了最大限度地发挥有限预算的影响，需要进行有效的优先事项设定。Optima TB 工具旨在支持分析能力，并为结核病健康福利套餐设计提供循证优先事项设定过程提供信息。本文概述了 Optima TB 框架以及如何在白俄罗斯（东欧一个中上收入国家，结核病负担相对较高）中应用该框架。Optima TB 是一种基于人群的疾病传播模型，具有项目成本函数和优化算法。模型化人群包括年龄不同的普通人群和艾滋病毒感染者等高危人群。人群和预期干预措施是在与当地利益相关者协商后确定的。然后与后者合作，为这些人群和干预措施收集人口统计、流行病学、项目以及成本和支出数据。在与当地利益相关者合作的情况下，使用协作中定义的目标和约束对白俄罗斯的结核病支出进行了优化分析，这些利益相关者包括专家、决策者、资助者以及参与服务提供、支持和技术援助的组织。这些分析表明，通过重新分配白俄罗斯目前的结核病支出，可以提高健康效果。具体而言，将资金从住院治疗模式转移到门诊治疗模式，从大规模筛查转移到主动病例发现策略，可以使 2035 年结核病的患病率和死亡率分别降低 45%和 50%。此外，优化结核病支出的分配可以使该期间耐多药结核病感染减少 40%。这将在不增加财政资源的情况下支持国家结核病目标的进展。白俄罗斯的案例研究表明，在现有和新干预措施之间重新分配支出可能会对结核病结果产生重大影响。这突出了 Optima TB 和类似建模工具支持循证优先事项设定的潜力。
