Using Whole Genome Sequencing to Decode Mycobacterium tuberculosis Transmission: application in a low-burden country

Abstract

Pág. 23 del libro de abstracts que se adjunta. With around 10 million new cases per year, tuberculosis (TB) is one of the most important infectious diseases in the world. Whole genome sequencing (WGS) is often used in TB surveillance programs due to its greater resolution compared to classical typing methods. Studies have demonstrated that WGS can identify outbreaks, predict transmission events and distinguish between relapses and co-infections. Despite this, the directionality of the transmission (whom infected whom) remains still uncertain. Here, we used WGS to identify, characterize and infer TB transmission in a low-incidence country during a three-year period. We applied phylogeographic approaches to identify and determine the date of endemic phylogenetic groups that are associated with Spanish-born transmission. Using pairwise nucleotide distances, we show a low concordance between WGS transmission and standard contact tracing method (40% vs 12.5%). Furthermore, we developed a model by combining epidemiological and genomic data to obtain estimates of the number of index cases and missing cases within clusters. This study improves the understanding of how and when TB transmits. In addition, it highlights the relevance of WGS data for improving disease control.