Spatially targeted interventions may be effective alternatives to individual or population-based prevention strategies against tuberculosis (TB). However, their efficacy may depend on the mechanisms that lead to geographically constrained hotspots. Local TB incidence may reflect high levels of local transmission; conversely, they may point to frequent travel of community members to high-risk areas. We used whole-genome sequencing to explore patterns of TB incidence and transmission in Lima, Peru. Between 2009 and 2012, we recruited incident pulmonary TB patients and their household contacts, whom we followed for the occurrence of TB disease. We used whole-genome sequences of 2,712 Mycobacterial tuberculosis isolates from 2,440 patients to estimate pariwise genomic distances and compared these to the spatial distance between patients' residences. Genomic distances increased rapidly as spatial distances increased and remained high beyond 2 km of separation. Next, we divided the study catchment area into 1 × 1 km grid-cell surface units and used household spatial coordinates to locate each TB patient to a specific cell. We estimated cell-specific transmission by calculating the proportion of patients in each cell with a pairwise genomic distance of 10 or fewer single-nucleotide polymorphisms. We found that cell-specific TB incidence and local transmission varied widely but that cell-specific TB incidence did not correlate closely with our estimates of local transmission (Cohen's k = 0.27). These findings indicate that an understanding of the spatial heterogeneity in the relative proportion of TB due to local transmission may help guide the implementation of spatially targeted interventions.
Keywords: genomic epidemiology; spatial analysis; transmission; tuberculosis; whole-genome sequence.