Mobility as a proxy for exposure to Mycobacterium tuberculosis in an African city with endemic tuberculosis

Tuberculosis remains a serious disease that persists around the world today because of ongoing transmission of Mycobacterium tuberculosis among cases and their contacts in the community. To curb the tuberculosis epidemic, new strategies are needed to reduce transmission in the community. Since quantifying exposures and transmission in a dynamic community is difficult, we propose that the mobility of a case during the infectious period may be a proxy measure of exposure and subsequent transmission. In a study performed in Kampala, Uganda, where the prevalence of tuberculosis disease was 750 cases/100,000 population, we collected cellular telephone call-detail records from 191 culture-confirmed tuberculosis cases and used a novel artificial intelligence algorithm, BERT4Traj, to estimate geographic trajectories of each case and characterized their mobility using metrics derived from the trajectories. We found that mobility of cases was both spatially and temporally heterogeneous. Some cases traced spatial patterns that bridged various locations and expanded their contact networks, whereas others traced regular movements that led to repeated contacts. This heterogeneity was partially explained by socio-demographic characteristics of the cases. The heterogeneity in the mobility of tuberculosis cases suggests that a single strategy to reduce transmission of tuberculosis may not suffice. Instead, future interventions should address the variable patterns of case mobility in the community.