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

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

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...

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Bibliographic Details
Main Authors: Kathryn Winglee, Clinton J. McDaniel, Lauren Linde, Steve Kammerer, Martin Cilnis, Kala M. Raz, Wendy Noboa, Jillian Knorr, Lauren Cowan, Sue Reynolds, James Posey, Jeanne Sullivan Meissner, Shameer Poonja, Tambi Shaw, Sarah Talarico, Benjamin J. Silk
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Public Health
Subjects:
tuberculosis
whole-genome sequencing
transmission
genomic epidemiology
cluster investigation
Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2021.667337/full

Internet

https://www.frontiersin.org/articles/10.3389/fpubh.2021.667337/full

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