Use of High-Resolution Geospatial and Genomic Data to Characterize Recent Tuberculosis Transmission, Botswana

Abstract

Combining genomic and geospatial data can be useful for understanding Mycobacterium tuberculosis transmission in high-burden tuberculosis (TB) settings. We performed whole-genome sequencing on M. tuberculosis DNA extracted from sputum cultures from a population-based TB study conducted in Gaborone, Botswana, during 2012–2016. We determined spatial distribution of cases on the basis of shared genotypes among isolates. We considered clusters of isolates with ≤5 single-nucleotide polymorphisms identified by whole-genome sequencing to indicate recent transmission and clusters of ≥10 persons to be outbreaks. We obtained both molecular and geospatial data for 946/1,449 (65%) participants with culture-confirmed TB; 62 persons belonged to 5 outbreaks of 10–19 persons each. We detected geospatial clustering in just 2 of those 5 outbreaks, suggesting heterogeneous spatial patterns. Our findings indicate that targeted interventions applied in smaller geographic areas of high-burden TB identified using integrated genomic and geospatial data might help interrupt TB transmission during outbreaks.

Keywords

• tuberculosis and other mycobacteria
• bacteria
• respiratory infections
• whole-genome sequencing
• spatial analysis
• geographic heterogeneity