P59
Genomic analysis in socially complex populations extracts valuable epidemiological information
C Rodríguez-Grande(1,2) S Vallejo-Godoy(3) M Martínez-Lirola(4) M Herranz(1,2,5) J A Garrido-Cárdenas(6) S Buenestado-Serrano(1,2) J P Escamez Berenguel(3) P Muñoz(1,2,5,7) L Pérez-Lago(1,2) D García de Viedma(1,2,5)
1:Laboratorio de Genómica Microbiana, Servicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, Madrid, 28007, España; 2:Grupo de Enfermedades Infecciosas, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, 28007, España; 3:USP Distrito Sanitario Poniente de Almería, Servicio Andaluz de Salud, Almería, 04700, España; 4:Servicio de Microbiología y Parasitología, Complejo Hospitalario Torrecárdenas, Almería, 04009, España; 5:CIBER Enfermedades Respiratorias (CIBERES), Servicio Madrileño de Salud, Hospital General Universitario Gregorio Marañón, Madrid, 28007, España; 6:Departamento de Biología y Geología, Universidad de Almería, 04120, España; 7:Departamento de Medicina, Facultad de Medicina, Universidad Complutense de Madrid, 28040, España
The analysis of tuberculosis transmission in socio-epidemiologically complex populations, with a high rate of migrants, demands refined approaches. We aimed to dissect more in-depth the true complexity within the clusters identified by population-based real-time 24-MIRU-VNTR analysis directly on clinical specimens in Almería, Spain. MIRU-VNTR-analysis was performed between 2005 and 2021 in 1290 cases (92%) from the 1403 culture positive cases diagnosed in Almería, Spain. 519 cases were included in 143 MIRU-VNTR-clusters. WGS analysis was performed on a selection of 33 clusters (23%; including 174 patients) representative of migrant, autochthonous and mixed clusters without an obvious epidemiological support. From the genomic data we could differentiate clusters due recent transmissions after arrival, from independent unrelated importations. In addition, star-like topologies, compatible with superspreading, were identified in the genomic relationships networks. Several clusters showed complex topologies (long branches with high number of SNPs between isolates and non-sampled nodes), suggesting transmission events involving a higher than suspected number of cases, both for migrant and autochthonous clusters. All these data led us to reorientate the interpretations initially obtained from the homogeneous MIRU-clusters and allowed us to infer valuable epidemiological information to tailor specific intervention strategies, according to the true nature of every transmission event.
This work was funded by the ISCIII (PI21/01823, PI19/00331, PFIS contract (FI20/00129)), Junta de Andalucía (AP-0062-2021-C2-F2) and European Regional Development Funds (FEDER) from the European Commission, “A way of making Europe”.