Exploring programmatic indicators of tuberculosis control that incorporate routine Mycobacterium tuberculosis sequencing in low incidence settings: a comprehensive (2017–2021) patient cohort analysis

Background Routine whole genome sequencing of Mycobacterium tuberculosis has been implemented with increasing frequency. However, its value for tuberculosis (TB) control programs beyond individual case management and enhanced drug resistance detection has not yet been explored.Methods We analysed routine sequencing data of culture-confirmed TB cases notified between 1st January 2017 and 31st December 2021 in New South Wales (NSW), Australia. Genomic surveillance included evidence of local TB transmission, defined by single nucleotide polymorphism (SNP) clustering over a variable (0-25) SNP threshold, and drug resistance conferring mutations.Findings M. tuberculosis sequences from 1831 patients were examined, representing 64.8% of all notified TB cases and 96.2% of culture-confirmed cases. Applying a traditional 5-SNP cluster threshold identified 62 transmission clusters with 183 clustered cases; 101/183 (55.2%) had 0 SNP differences. Cluster assessment over a 5-year period, using a 5-SNP threshold, provided a comprehensive overview of likely recent transmission within NSW, Australia, as an indicator of local TB control. Genotypic drug susceptibility testing (DST) was highly concordant with phenotypic DST and provided a 6.8% increase in antimycobacterial resistance detection. Importantly, it detected mutations missed by routine molecular tests. Lineage 2 strains were more likely to be drug resistant (p < 0.0001) and locally transmitted if drug resistant (p < 0.0001).Interpretation Performing routine prospective WGS in a low incidence country like Australia, provides genomically informed programmatic indicators of local TB control. A rolling 5-year cluster assessment reflects epidemic containment and progress towards 'zero TB transmission'. Genomic DST also provides valuable information for clinical care and drug resistance surveillance. Copyright (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).