Fig 1.
Schematic of an Optima TB analysis (source: OCDS).
Fig 2.
Structure of the epidemiological model at the core of Optima TB.
Square boxes in the figure represent compartments, or population sizes, at a given point in time. Ellipses represent junctions, which unlike compartments do not represent population sizes, and only enable the ‘filtering’ of flows of latent activations into either smear-positive or smear-negative, and subsequently into drug-susceptible or a form of drug-resistant TB. Solid lines between boxes and ellipses represent transition rates, or the probability of moving from one compartment to another, within a given timeframe. Dashed lines represent specific transition rates relating to the probability of interrupted treatment or developing multi-drug resistant or extensively drug-resistant TB while on-treatment.
Table 1.
Key population statistics.
Fig 3.
(a) Datapoints are UN Population Division estimates (2000–2015) [49], (b) and (c) datapoints are WHO active TB prevalence upper-bound estimates disaggregated by population group (2000–2014) [53] and (d) shaded area represents confidence intervals of WHO active TB prevalence estimates for total population (2000–2014) [53].
Table 2.
Interventions included in the Belarus analysis.
Table 3.
Interventions with defined constraints in the optimisation analysis.
Fig 4.
National TB spending in Belarus in 2015 compared with optimised annual budget to minimise active TB prevalence and incidence and TB-related mortality by 2035.
Fig 5.
Projected impact of 2015 and optimised allocations of national TB spending on key TB indicators among HIV-negative adults and people living with HIV from 2015 to 2035.
Fig 6.
Progress toward national and global TB targets for (a) TB mortality and (b) new TB infections in the 15–64 age group, under 2015 and optimised allocations of national TB spending.