Assessing tuberculosis control priorities in high-burden settings: a modelling approach

Area of Science:

• Public Health
• Epidemiology
• Mathematical Modeling

Background:

• The World Health Organization's End TB strategy necessitates focused control efforts on effective interventions.
• Accelerating tuberculosis (TB) burden reduction requires identifying high-impact innovations.

Purpose of the Study:

• To identify which improvements in the TB care cascade would most effectively reduce TB incidence and mortality.
• To link TB care cascade performance to disease transmission dynamics.

Main Methods:

• A modeling approach was used to connect the TB care cascade with disease transmission.
• Data from national TB programs in India, Kenya, and Moldova were analyzed.
• Bayesian melding was employed within a mathematical model to assess cascade shortfalls' impact.

Main Results:

• Combined cascade improvements could reduce cumulative TB incidence by 27-38% between 2018-2035 across study settings.
• Key losses identified: private sector engagement (India), missed diagnosis (Kenya), drug sensitivity testing (Moldova).
• The most significant delay impacting outcomes is the time to initial patient presentation for care.

Conclusions:

• The TB care cascade, linked to transmission, is vital for improving patient outcomes.
• It aids in identifying and monitoring programmatic priorities to reduce TB incidence and mortality.
• The proportion of individuals on high-quality treatment may be a more robust monitoring tool than routine notifications.