摘要
目的了解苏州市肺结核的流行特点和各县区的时空变化特征, 为制定防控策略提供数据支持。方法通过"中国疾病预防控制信息系统"收集2013—2021年苏州市登记患者数据。采用趋势性χ^(2)检验分析2013—2021年肺结核发病率的变化趋势。采用描述性研究分析肺结核的流行特征;采用空间自相关分析和空间聚集模型对肺结核的登记数据作空间变化分析, 确定防控的冷热点地区。结果 2013—2021年, 苏州市共登记30 649例肺结核患者, 年均登记发病率为27.23/10万;各年度的登记发病率在(23.78~31.30)/10万之间, 发病率总体呈下降趋势(χ^(2)趋势=190.118, P<0.001)。苏州市肺结核发病1~4季度的季节指数分别为87.87%、112.50%、113.81%和89.62%。据发病率可视化地图, 常熟市(31.78/10万)、太仓市(31.93/10万)为高发病率县市(区), 中心城区的姑苏区(14.82/10万)、苏州工业园区(20.16/10万)等区域是低发区。空间自相关模型分析显示, 2016、2019和2021年苏州市肺结核发病总体上呈空间聚集效应(全局Moran’sI值为0.422~0.493, P均<0.05)。热点分析表明, 苏州工业园区、相城区、姑苏区长期作为发病冷点区或次冷点区, 常熟市和太仓市为发病热点区。结论 2013—2021年, 苏州市肺结核的发病率显著下降, 防控效果良好。苏州市的常熟市、太仓市、昆山市、张家港市等的县市呈现发病聚集特征, 以上县市也是发病热点区。今后应引导医疗卫生资源向发病的热点区域合理倾斜。
Objective To understand the epidemiological characteristics and spatio-temporal variations of tuberculosis in Suzhou City,so as to provide theoretical basis for improving the prevention and control strategy of tuberculosis.Methods Data of registered tuberculosis cases in Suzhou City from 2013 to 2021 were collected through a sub-system of the Chinese Disease Prevention and Control Information System.The trend of tuberculosis incidence from 2013 to 2021 was analyzed byχ^(2) trend analysis.Descriptive analysis was used to investigate the epidemic characteristics of tuberculosis.Spatial autocorrelation analysis and spatial aggregation model were applied to analyze the spatial changes of tuberculosis,and identify the hot and cold regions for prevention.Results A total of 30649 patients with tuberculosis were registered in Suzhou from 2013 to 2021,with an average annual incidence of 27.23 per 100000.The annual incidence rates ranged from 23.78 per 100000 to 31.30 per 100000,with a downward trend(χ^(2)trend=190.118,P<0.001).The seasonal indexes of tuberculosis incidence from the first to fourth quarter were 87.87%,112.50%,113.81%and 89.62%,respectively.According to the ArcGIS incidence map,Changshu City(31.78 per 100000)and Taicang City(31.93 per 100000)were high incidence areas,while Gusu District(14.82 per 100000)and Suzhou Industrial Park(20.16 per 100000)in the central city were low incidence areas.Spatial autocorrelation model analysis showed a spatial aggregation effect of tuberculosis incidence in Suzhou City in 2016,2019 and 2021(global Moran's I values were 0.422-0.493,all P<0.05).Hotspot analysis showed that Suzhou Industrial Park,Xiangcheng District and Gusu District were long-term cold area or sub-cold spot areas,while Changshu City and Taicang City were hotspot areas.Conclusions From 2013 to 2021,the incidence of tuberculosis decreased significantly in Suzhou City,indicating that the prevention and control measures are effective.Changshu City,Taicang City,Kunshan City and Zhangjiagang City show clusterin
作者
丁邱
李云
张晓龙
蒋骏
Ding Qiu;Li Yun;Zhang Xiaolong;Jiang Jun(Department of Tuberculosis Control,Suzhou Center for Disease Prevention and Control,Suzhou 215026,China)
出处
《国际流行病学传染病学杂志》
CAS
2023年第6期386-390,共5页
International Journal of Epidemiology and Infectious Disease
基金
苏州市重大疾病、传染病预防与控制关键技术研究项目(GWZX202001)。
关键词
结核
肺
空间聚集性
空间自相关
热点分析
季节指数
Tuberculosis,pulmonary
Spatial aggregation
Spatial autocorrelation analysis
Hotspot analysis
Seasonal index
