LITT

The Logically Inferred Tuberculosis Transmission (LITT) algorithm is a tool to enhance the understanding and intervention strategies for tuberculosis (TB) transmission chains. It achieves this by automating the integration and analysis of whole-genome sequencing alongside clinical and epidemiological data. Traditionally, identifying potential source cases within TB clusters required labor-intensive, manual investigations. LITT streamlines this process by systematically identifying and ranking potential source cases for each individual within a cluster, thereby aiding public health professionals in targeting resources more effectively to prevent further transmission.

To facilitate the adoption and use of LITT by frontline public health staff, the development team also created a graphical user interface, a comprehensive user manual, and training resources. While recognizing that LITT cannot wholly replace detailed field investigations, its developers emphasize the tool's capacity to support public health professionals by offering a systematic approach to analyzing and interpreting complex data during TB cluster investigations.