A long-term refined genomic analysis of tuberculosis clusters to discriminate between ongoing transmission, reactivations or diagnostic delays

Introduction Tuberculosis (TB) clusters are interpreted as ongoing transmission events, which demand control interventions. Our aim is to perform a refined genomic analysis in Almería, Spain, to evaluate whether reasons other than ongoing transmission could be behind the incorporation of new cases to pre-existing or new clusters, to manage more properly each new clustered case and optimizing control resources. Methods Illumina WGS was performed following standard procedures. First, genomic data were analyzed quantitatively, to identify clustered cases (< 12 SNPs). Then, a refined evolutionary analysis was performed, positioning the clustered cases in genomic networks, based on the distribution of SNPs. The location of the new clustered cases in relation to the cases preceding it in the cluster was considered to interpret the most likely reasons behind the growth of each cluster, supporting them by epidemiological and clinical data. Results We identified 106 genomic clusters during the years 2003–2024, including a total of 537 cases (2–25 cases/cluster). 106 (34.6%) of the diagnosed cases in the last four years (2021–2024) were included in 53 clusters; 22 were new clusters, while the remaining were growing clusters, already identified before 2021. New entrances in clusters were due to ongoing transmission (new cases connected in the genomic network with a recently diagnosed case at 0–2 SNPs) in only 29% of the growing clusters (1–11 cases entering in pre-existing clusters) and in 63.6% of the new clusters (2–6 cases/cluster). For new clustered cases who were not the result of ongoing transmission, the analysis of the genomic networks allowed us to identify clusters with the involvement of i) reactivations of past exposures (new case close to another case diagnosed > 4 years before), ii) prolonged diagnostic delays or subclinical periods (new case positioned in branches with a high number of SNPs preceding them, suggesting persistent bacterial viability), or to iii) multifactorial clusters, growing by reactivations, diagnostic delays and/or ongoing transmission. Conclusion A genomic evolutionary analysis is required for a precise interpretation of growing clusters. Only one-third of the growing clusters in Almería correspond to ongoing transmissions. Reactivations of past exposures, prolonged diagnostic delays or subclinical TB had also a role in growing clusters. The precise identification of the reasons behind growing clusters allows the specific management of each new clustered case.