Long-term refined genomic analysis of tuberculosis clusters to distinguish between ongoing transmission, reactivations or diagnostic delays, Almería, Spain, 2003 to 2024

BACKGROUND In tuberculosis (TB) surveillance, genomics is mainly used to identify TB patient clusters; growing clusters are commonly attributed to ongoing transmission events. AIM This study’s objective was to explore other factors, in addition to ongoing transmission, contributing to cluster expansion. METHODS The study population included all 1,886 culture-positive TB cases diagnosed within the whole Almería province population, Spain, between January 2003 and June 2024. Cases’ Mycobacterium tuberculosis strains were whole genome sequenced enabling detection of clusters (with pairwise distance between strains < 12 single nucleotide polymorphisms (SNPs)). Evolutionary analyses positioned cases within genomic networks based on SNP distribution. This allowed, together with clinical and epidemiological data, to infer why new cases (diagnosed 3.5 years prior) entered clusters. RESULTS Cases’ mean age was 37.3 years (standard deviation: 16.4); 71.7% (1,352/1,886) were male and 65.2% (1,230/1,886) migrants from 50 countries, with mostly Moroccan (21.6%; 407/1,886), Romanian (10%; 188/1,886), Senegalese (8.3%; 156/1,886) and Malian (5.2%; 98/1,886) nationalities. We detected 106 clusters, comprising 537 cases in total. The 106 new cases occurred within 53 clusters, including 31 growing clusters (identified pre-2021) and 22 recent clusters (that arose in 2021 and after). Ongoing transmission was responsible for cluster expansion in around one-third of growing clusters (9/31), versus two-thirds (15/22) of recent clusters. Genomic network assessments found that newly clustered cases not due to ongoing transmission, were likely driven by reactivation of past exposures, prolonged diagnostic delays or subclinical periods, or a combination of these factors. CONCLUSION Understanding cluster dynamics guides case-specific management and supports TB control.