Characteristics of Plausible Source Cases Responsible for Recent Mycobacterium tuberculosis Transmission, United...

Tuberculosis (TB) outbreaks in the United States can cause substantial illness. Using surveillance and genotyping data, we applied a plausible source-case algorithm to identify TB cases reported during 2018-2020 responsible for secondary cases attributed to recent Mycobacterium tuberculosis transmission during 2020-2022. We used mixed models and a machine learning workflow to assess sociodemographic, clinical, and social risk factors associated with plausible sources. In mixed models, sputum smear positivity, cavitary disease, race/ethnicity other than non-Hispanic White or non-Hispanic Asian, age <65 years, US birth, and homelessness were associated with plausible sources. An adaptive boosting model achieved an area under the receiver operating characteristic curve of 0.81 on test data. Transmission was heterogeneous; 8.1% of sources linked to 3-15 secondary cases accounted for 24.9% of transmission events. Focusing case management and contact investigations on cases with the characteristics we identified could reduce M. tuberculosis transmission and improve TB prevention.