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南非德班地区广泛耐药结核病“热点”及其与社会人口学的关联。

Extensively drug-resistant tuberculosis 'hotspots' and sociodemographic associations in Durban, South Africa.

机构信息

Emory University Rollins School of Public Health, Atlanta, Georgia.

Emory University Rollins School of Public Health, Atlanta, Georgia, Emory University School of Medicine, Atlanta, Georgia, USA.

出版信息

Int J Tuberc Lung Dis. 2019 Jun 1;23(6):720-727. doi: 10.5588/ijtld.18.0575.

Abstract

BACKGROUND 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. METHODS 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. RESULTS 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. CONCLUSIONS 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. .

摘要

背景 在南非夸祖鲁-纳塔尔省,广泛耐药结核病(XDR-TB)的发病率是由耐药菌株的传播驱动的。由于数据表明病例可能呈空间聚集,我们试图确定“热点”并描述这些社区。 方法 我们在埃滕哈赫温招募了 2011 年至 2014 年间诊断出的 XDR-TB 患者。收集了参与者家庭的全球定位系统(GPS)坐标,并根据人口调整后的 XDR-TB 发病率确定了热点。使用人口普查数据描述热点的社会人口学特征。对于一部分参与者,我们绘制了非家庭 XDR-TB 聚集地点的地图,并将这些结果与仅包括家庭的结果进行了比较。 结果 在 132 名参与者中,75 名(57%)为女性,87 名(66%)居住在城市或郊区。在 197 个普查区中有 15 个被确定为 XDR-TB 热点,置信度为 95%。四种空间绘图方法确定了埃滕哈赫温东北部的一个大型热点。热点社区的低教育程度比例较高(12%比 9%),失业率较高(29.3%比 20.4%),冲水厕所比例较低(36.4%比 68.9%)。当对 43 名(33%)参与者的聚集地点(如工作场所)进行映射时,病例密度向德班市中心转移。 结论 在埃滕哈赫温,XDR-TB 病例家庭聚集在热点社区,这些社区的贫困指标比非热点社区更多。针对热点社区和聚集场所的预防措施可能会有效减少社区传播。 .

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