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Extensively drug-resistant tuberculosis ‘hotspots' and sociodemographic associations in Durban, South Africa
22
Citations
21
References
2019
Year
Tuberculosis PreventionDisease MappingEpidemiologic ResearchPopulation Health SciencesHotspot CommunitiesDrug ResistanceGlobal Positioning SystemClinical EpidemiologySouth AfricaMedical AnthropologyEpidemiologic MethodPublic HealthTuberculosis DiagnosticsSpatial EpidemiologyPopulationAfrican DevelopmentInfectious Disease EpidemiologyPulmonary TuberculosisHealth GeographyTuberculosisEpidemiologySociodemographic AssociationsGlobal HealthRural HealthMedicine
<sec> <title>BACKGROUND</title> In KwaZulu-Natal, South Africa, the incidence of extensively drug-resistant tuberculosis (XDR-TB) is driven by the transmission of resistant strains. As data suggest that cases may be spatially clustered, we sought to identify 'hotspots' and describe these communities. </sec> <sec> <title>METHODS</title> We enrolled XDR-TB patients diagnosed from 2011 to 2014 in eThekwini. Global positioning system (GPS) coordinates for participant homes were collected and hotspots were identified based on population-adjusted XDR-TB incidence. The sociodemographic features of hotspots were characterised using census data. For a subset of participants, we mapped non-home XDR-TB congregate locations and compared these with results including only homes. </sec> <sec> <title>RESULTS</title> Among 132 participants, 75 (57%) were female and 87 (66%) lived in urban or suburban locations. Fifteen of 197 census tracts were identified as XDR-TB hotspots with ≥95% confidence. Four spatial mapping methods identified one large hotspot in northeastern eThekwini. Hotspot communities had higher proportions of low educational attainment (12% vs. 9%) and unemployment (29.3% vs. 20.4%), and lower proportion of homes with flush toilets (36.4% vs. 68.9%). The case density shifted towards downtown Durban when congregate locations (e.g., workplaces) for 43 (33%) participants were mapped. </sec> <sec> <title>CONCLUSIONS</title> In eThekwini, XDR-TB case homes were clustered into hotspots with more poverty indicators than non-hotspots. Prevention efforts targeting hotspot communities and congregate settings may be effective in reducing community transmission. </sec>.
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