上海松江2006-2011年新登记肺结核时空分布规律及影响因素

目的 了解上海市松江区2006-2011年新登记肺结核(tuberculosis,TB)的时空分布规律及其影响因素.方法 收集2006-2011年TB相关信息,应用时空扫描统计量探测TB的时空聚集区,应用Logistic回归模型分析影响TB聚集区形成的危险因素.结果 松江区2006-2011年新登记2 916例TB,单纯空间扫描统计显示全部TB及全部菌阳TB均在车墩镇聚集,本地TB及本地菌阳TB的空间聚集区为西南部的五个镇(新浜、石湖荡、小昆山、泖港和永丰),流动TB的聚集区为车墩镇,流动菌阳TB的聚集区为车墩镇、叶榭镇和泖港镇.时空扫描统计量显示松江区肺结核病例在2007-2008年出现聚集现象,聚集区域为工业区所在地的车墩镇和新桥镇.对于本地患者,农民职业者及就诊延误与空间聚集区呈独立相关;流动患者中,职业为蓝领工人、年龄小于60岁及来源于中国中西部地区是形成空间聚集区的危险因素.结论 松江区TB的分布具有一定的时空聚集性.东部工业区是流动TB的聚集区域,西南五镇是本地TB的聚集区域,TB防控的工作重点应聚焦于这些区域;流动人口是TB聚集的重要因素,应重点关注.

Spatio-temporal patterns and risk factors of tuberculosis clustering between 2006 and 2011 in Songjiang District,Shanghai

Objective To identify the spatio-temporal distribution patterns and risk factors of tuberculosis （TB） between 2006 and 2011 in Songjiang District, Shanghai. Methods All active TB cases and all bacteriologically confirmed TB cases between 2006 and 2011 were collected in the study. Space-time scan statistics was used to identify spatial clusters. Logistic regression was used to compared the demographic and clinical characteristics of TB cases in spatial clusters versus TB cases not in spatial clusters. Results A total of 2 916 active TB cases were eligible for analysis during 2006 - 2011. Purely spatial scan statistics showed clusters that were all located in Cheduu both for active TB cases and bacteriolog- ically confirmed cases. For local residents with active TB and local bacteriologically confirmed cases, clusters were identi- fied in five communities/towns （Xinbang, Shihudang, Xiao Kunshan, Maogang and Yongfeng） in the southwest areas. The urban migrant patients were clustered in Chedun, while sputum positive migrant cases were clustered in Chedun, Yexie and Maogang. Logistic regression analysis showed that the farmers and those with delaged treatment were independently associ- ated with clustering for local resident patients. For urban migrant patients, blue-collar workers, and persons younger than 60 years and immigrants from western regions were the risk factors of spatial clustering. Conclusions Spatial and temporal clusters have been identified in industrial zone and five communities/towns in southwestern of Songjiang District. Interventions to prevent the secondary transmission should be focused on these areas, especially for urban migrants.