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Nelson, K.

Publications and source records attributed to Nelson, K..

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Microbial Metagenome Of Urinary Tract Infection

Urine culture and microscopy techniques are used to profile the bacterial species present in urinary tract infections. To gain insight into the urinary flora in infection and health, we analyzed clinical laboratory features and the microbial metagenome of 121 clean-catch urine samples. 16S rDNA gene signatures were successfully obtained for 116 participants, while whole genome shotgun sequencing data was successfully generated for samples from 49 participants. Analysis of these datasets supports the definition of the patterns of infection and colonization/contamination. Although 16S rDNA sequencing was more sensitive, whole genome shotgun sequencing allowed for a more comprehensive and unbiased representation of the microbial flora, including eukarya and viral pathogens, and of bacterial virulence factors. Urine samples positive by whole genome shotgun sequencing contained a plethora of bacterial (median 41 genera/sample), eukarya (median 2 species/sample) and viral sequences (median 3 viruses/sample). Genomic analyses revealed cases of infection with potential pathogens (e.g., Alloscardovia sp, Actinotignum sp, Ureaplasma sp) that are often missed during routine urine culture due to species specific growth requirements. We also observed gender differences in the microbial metagenome. While conventional microbiological methods are inadequate to identify a large diversity of microbial species that are present in urine, genomic approaches appear to comprehensively and quantitatively describe the urinary microbiome.

microbiology

Spatial distribution of extensively drug-resistant tuberculosis (XDR-TB) patients in KwaZulu-Natal, South Africa

BackgroundKwaZulu-Natal province, South Africa, has among the highest burden of XDR-TB worldwide with the majority of cases occurring due to transmission. Poor access to health facilities can be a barrier to timely diagnosis and treatment of TB, which can contribute to ongoing transmission. We sought to determine the geographic distribution of XDR-TB patients and proximity to health facilities in KwaZulu-Natal.\n\nMethodsWe recruited adults and children with XDR-TB diagnosed in KwaZulu-Natal. We calculated distance and time from participants home to the closest hospital or clinic, as well as to the actual facility that diagnosed XDR-TB, using tools within ArcGIS Network analyst. Speed of travel was assigned to road classes based on Department of Transport regulations. Results were compared to guidelines for the provision of social facilities in South Africa: 5km to a clinic and 30km to a hospital.\n\nResultsDuring 2011-2014, 1027 new XDR-TB cases were diagnosed throughout all 11 districts of KwaZulu-Natal, of whom 404 (39%) were enrolled and had geospatial data collected. Participants would have had to travel a mean distance of 2.9 km (CI 95%: 1.8-4.1) to the nearest clinic and 17.6 km (CI 95%: 11.4-23.8) to the nearest hospital. Actual distances that participants travelled to the health facility that diagnosed XDR-TB ranged from <10 km (n=143, 36%) to >50 km (n=109, 27%). The majority (77%) of participants travelled farther than the recommended distance to a clinic (5 km) and 39% travelled farther than the recommended distance to a hospital (30 km). Nearly half (46%) of participants were diagnosed at a health facility in eThekwini district, of whom, 36% resided outside the Durban metropolitan area.\n\nConclusionsXDR-TB cases are widely distributed throughout KwaZulu-Natal province with a denser focus in eThekwini district. Patients travelled long distances to the health facility where they were diagnosed with XDR-TB, suggesting a potential role for migration or transportation in the XDR-TB epidemic.

epidemiology