Active tuberculosis case finding in India - The way forward.

Area of Science:

• Public Health
• Infectious Disease Epidemiology
• Global Health

Background:

• Community-based active case finding (ACF) is a key strategy for tuberculosis (TB) elimination.
• Various ACF algorithms are employed in India, with evolving diagnostic tools.

Purpose of the Study:

• To evaluate the accuracy and cost-effectiveness of different ACF algorithms for TB detection in India.
• To inform optimal selection of diagnostic algorithms based on prevalence, accuracy, and resources.

Main Methods:

• Analysis of sensitivity and specificity of screening and diagnostic tools from community-based surveys.
• Review of current and potential ACF algorithms used in India.

Main Results:

• ACF is most effective when prioritized for high-prevalence settings.
• Chest X-ray alone is insufficient; sputum smear positivity is required.
• Xpert MTB/RIF accuracy in community settings requires further investigation.
• Significant patient default rates were observed in ACF-detected TB cases.

Conclusions:

• Diagnostic algorithm choice for ACF should balance prevalence, accuracy, and resource availability.
• Addressing patient default is crucial for successful ACF programs.
• Prioritizing sensitive diagnostics and ACF in high-risk groups will enhance early TB detection.