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However, the nationwide spatial distribution and transmission dynamics of RR\/MDR-TB remain poorly characterised. This study aims to analyse spatial patterns of RR\/MDR-TB in Rwanda and explore relationships between spatial proximity and RR\/MDR-TB strains\u2019 genetic relatedness.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective analysis of 249 confirmed RR-TB cases across Rwanda from 2017 to 2024, using the known geolocations of patients\u2019 residences. Spatial and space-time clustering was assessed using Kulldorff\u2019s scan statistics. Demographic and socioeconomic determinants were evaluated using multivariable regression. For 201 cases with whole-genome sequencing data, we performed transmission analysis using a 5-SNP threshold to define recent transmission clusters and investigated spatial relationships within genetically related strains.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Significant spatial clustering of RR\/MDR-TB was identified in 21 sectors, mainly in Nyarugenge, southern Gasabo and western Kicukiro (relative risk: 10.06; p&lt;0.001). Our multivariable analysis showed that population density is positively associated with case notification rates. Molecular analysis revealed 88.5% of cases belonged to genotype clusters defined using a 12-SNP threshold, with 73.6% forming clusters at a strict 5-SNP threshold. Spatial K-function analysis of the six major clusters revealed heterogeneous transmission patterns, characterised by both tightly clustered outbreaks and regional transmission networks that spanned administrative boundaries. Most clusters (5\/6) extended beyond Kigali, indicating that transmission networks operate across administrative divides.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>RR\/MDR-TB in Rwanda shows significant spatial clustering with transmission occurring through both localised and regional networks. Integrating genomic and spatial data reveals transmission patterns that extend beyond household contacts and administrative boundaries. These findings underscore the need to implement geographically targeted interventions that address community-level transmission to control RR\/MDR-TB in Rwanda effectively.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjopen-2025-111823","type":"journal-article","created":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T10:40:23Z","timestamp":1787740823000},"page":"e111823","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Spatial clustering and transmission networks of multidrug-resistant tuberculosis in Rwanda: a national retrospective genomic and spatial epidemiological study"],"prefix":"10.1136","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7543-3386","authenticated-orcid":false,"given":"Isabel","family":"Cuella-Martin","sequence":"first","affiliation":[{"name":"Unit of Mycobacteriology, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, 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