Quantifying progression and regression across the spectrum of pulmonary tuberculosis: a data synthesis study

Area of Science:

• Epidemiology
• Mathematical Modeling
• Infectious Disease Dynamics

Background:

• Subclinical tuberculosis presents a significant public health burden, with individuals progressing, regressing, or persisting with the disease.
• Understanding the natural history and transition pathways of tuberculosis disease is crucial for effective control strategies.

Purpose of the Study:

• To quantify the progression, regression, and persistence pathways across the spectrum of untreated tuberculosis disease.
• To estimate the rates of transition between minimal, subclinical, and clinical tuberculosis states.

Main Methods:

• Developed a deterministic framework modeling untreated tuberculosis progression between minimal, subclinical, and clinical states.
• Utilized a Bayesian framework with data from a systematic review of 22 studies (5942 individuals) to estimate transition rates and uncertainty intervals.
• Quantified disease pathways and outcomes over 5 and 10-year periods.

Main Results:

• After 5 years, 40% of individuals with subclinical tuberculosis recover, 18% die, and 14% remain infectious.
• Over 5 years, 50% of those with subclinical tuberculosis never develop symptoms.
• Estimated 10-year mortality for untreated infectious tuberculosis at 37%.

Conclusions:

• Subclinical tuberculosis does not inevitably lead to symptomatic clinical disease.
• Relying solely on symptom-based screening may fail to detect a substantial proportion of infectious individuals.
• Quantifying disease pathways is essential for understanding tuberculosis epidemiology and informing public health interventions.