Logically Inferred Tuberculosis Transmission (LITT): A Data Integration Algorithm to Rank Potential Source Cases

• Main Authors: Kathryn Winglee (Author), Clinton J. McDaniel (Author), Lauren Linde (Author), Steve Kammerer (Author), Martin Cilnis (Author), Kala M. Raz (Author), Wendy Noboa (Author), Jillian Knorr (Author), Lauren Cowan (Author), Sue Reynolds (Author), James Posey (Author), Jeanne Sullivan Meissner (Author), Shameer Poonja (Author), Tambi Shaw (Author), Sarah Talarico (Author), Benjamin J. Silk (Author)
• Formato: Libro
• Publicado: Frontiers Media S.A., 2021-06-01T00:00:00Z.
• Subjects: article
• Acceso en liña: Connect to this object online.

Understanding tuberculosis (TB) transmission chains can help public health staff target their resources to prevent further transmission, but currently there are few tools to automate this process. We have developed the Logically Inferred Tuberculosis Transmission (LITT) algorithm to systematize the...