2013-2016年上海市浦东新区一二期梅毒时空扫描分析
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摘要
目的了解上海市浦东新区2013-2016年一二期梅毒的时空分布规律,为梅毒防控措施的科学制定提供参考依据。方法梅毒的发病数据来源于传染病报告信息系统,浦东新区各街镇的人口数来源于上海浦东统计年鉴,街镇的边界地图使用国家测绘局2015年版shp格式的地图数据。采用Excel 2010和SPSS 22整理分析数据,采用Sa TScan9.3的回顾法泊松模型进行时空聚集性扫描,采用Arc GIS 10.5将扫描结果可视化。检验水准取0.05。结果上海市浦东新区2013-2016年一二期梅毒的发病率分别为45.78/10万、40.91/10万、40.49/10万、39.09/10万,发病类型以一期梅毒为主,占58.57%,性别以男性为主,占64.14%,年龄以20～60岁的青壮年为主,占77.65%。发病时间具有一定的波动性,在每年的8月份左右出现发病的高峰,高峰月份的发病人数呈缓慢下降的趋势(趋势卡方检验X~2=0.001,P=0.047)。发病时间聚集出现在2013年1月1日-2013年9月21日期间。发病率相对较高的区域包括高桥、塘桥、三林、周浦等地,具有统计学意义的空间聚集区域有7个、时空聚集区域有3个(P<0.05)。结论通过对一二期梅毒的时空聚集性研究,可为梅毒防控措施的科学制定及卫生资源的优化配置提供一定参考。
Objective To understand the temporal and spatial distribution of syphilis during the period from 2013 to 2016 in Shanghai Pudong New Area, and to provide reference for the scientific formulation of syphilis control measures. Methods The incidence data of syphilis originated from the infectious disease report information system. The population of town in Pudong New District was derived from the Shanghai Pudong Statistical Yearbook, and the town boundary map was used in the map data of the 2015 edition of shp file format of the State Bureau of Surveying and Mapping. Using Excel 2010 and SPSS 22 to collate analysis data, and using the retrospective method of SaTScan 9.3 to conduct spatio-temporal clustering scans, ArcGIS10.5 was used to visualize the scan results. α=0.05. Results The incidence of syphilis in the Pudong New Area of Shanghai from 2013 to 2016 was 45.78 per 100,000, 40.91 per 100,000, 40.49 per 100,000 and 39.09 per 100,000. The incidence of syphilis was main(58.57%), Gender is dominated by males(64.14%), and age is dominated by young adults between 20 and60 years old(77.65%). The time of onset has a certain degree of volatility. The peak of onset occurs around August of each year, and the number of people suffering from the onset of peak months is slowly declining(trend chi-square test X~2=0.001,P=0.047). The temporal clustering occurred between January 1, 2013 and September 21, 2013. The areas with relatively high incidence include Gaoqiao, Tangqiao, Sanlin and Zhoupu. There are 7 statistically significant spatial clusters and 3 temporal and spatial clusters(P <0.05). Conclusion Through the research on the temporal and spatial aggregation of primary and secondary syphilis, it provides some reference for the scientific formulation of syphilis control measures and the optimal allocation of health resources.
Objective To understand the temporal and spatial distribution of syphilis during the period from 2013 to 2016 in Shanghai Pudong New Area, and to provide reference for the scientific formulation of syphilis control measures. Methods The incidence data of syphilis originated from the infectious disease report information system. The population of town in Pudong New District was derived from the Shanghai Pudong Statistical Yearbook, and the town boundary map was used in the map data of the 2015 edition of shp file format of the State Bureau of Surveying and Mapping. Using Excel 2010 and SPSS 22 to collate analysis data, and using the retrospective method of SaTScan 9.3 to conduct spatio-temporal clustering scans, ArcGIS10.5 was used to visualize the scan results. α=0.05. Results The incidence of syphilis in the Pudong New Area of Shanghai from 2013 to 2016 was 45.78 per 100,000, 40.91 per 100,000, 40.49 per 100,000 and 39.09 per 100,000. The incidence of syphilis was main(58.57%), Gender is dominated by males(64.14%), and age is dominated by young adults between 20 and60 years old(77.65%). The time of onset has a certain degree of volatility. The peak of onset occurs around August of each year, and the number of people suffering from the onset of peak months is slowly declining(trend chi-square test X~2=0.001,P=0.047). The temporal clustering occurred between January 1, 2013 and September 21, 2013. The areas with relatively high incidence include Gaoqiao, Tangqiao, Sanlin and Zhoupu. There are 7 statistically significant spatial clusters and 3 temporal and spatial clusters(P <0.05). Conclusion Through the research on the temporal and spatial aggregation of primary and secondary syphilis, it provides some reference for the scientific formulation of syphilis control measures and the optimal allocation of health resources.
引文
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[14]来明月,王江宁,王宇.西双版纳州2010~2015年梅毒流行特征分析[J].皮肤病与性病,2016,38(6):431-434.
[15]高守芝,陈曦,贺健梅,等.湖南省部分医疗机构梅毒和淋病病例报告与诊断调查[J].实用预防医学,2011,18(10):1865-1867.
[16]陈晨春,唐咸艳.2008-2013年南宁市梅毒小尺度的时空聚集性研究[J].中国皮肤性病学杂志,2015,29(7):699-703.
[17]杨振,王念,王宇.中国性病疫情的时空差异与经济驱动机制--以淋病、梅毒为例[J].热带地理,2016,36(5):761-766.
[2]关鹏,曹爽,黄德生,等.2005-2011年中国大陆地区梅毒疫情时空分布[J].中国感染控制杂志,2014,13(5):257-262.
[3]李思,朱渭萍,陆一涵,等.应用Sa TScan与Fle XScan识别丙型肝炎发病的高风险区域[J].中华疾病控制杂志,2017,21(8):805-808, 817.
[4] Tango T, Takahashi K. A flexibly shaped spatial scan statistic for detecting clusters[J]. International Journal of Health Geographics,2005, 4:11.
[5]赵鹏鹏,胡锦流,孙修福,等.2006-2015年江苏淮安市梅毒流行病学特征分析[J].公共卫生与预防医学,2017,28(4):73-76.
[6]赵淑娟,黄丽丽,杨杰.2009-2016年许昌市梅毒流行趋势分析[J].现代预防医学,2017,44(14):2503-2506.
[7]杨再新.2015年本溪市法定报告传染病疫情分析[J].职业与健康,2017,33(14):1948-1951.
[8]张建东,李娜.2012-2016年固原市甲乙类传染病疫情流行趋势分析[J].宁夏医学杂志,2017,39(6):569-570.
[9]孟晓军,张轩,成浩,等.无锡市2006-2015年梅毒流行特征与趋势分析[J].中国艾滋病性病,2016,22(11):904-907.
[10]王振平.丰县2010-2015年梅毒流行病学分析[J].华南预防医学,2017,43(1):50-51.
[11]方清艳,张婉悦,杨志芳,等.2011-2015年云南省梅毒流行病学分析[J].中国皮肤性病学杂志,2017,31(2):177-179, 182.
[12]相晓妹,李熙桐,杜晓婷,等.2005-2014年西安市梅毒及淋病流行病学分析[J].现代预防医学,2017,44(6):972-975, 982.
[13]马依拉,吴剑波,迪丽娜尔.2010-2015年新疆博乐市梅毒流行病学特征分析[J].公共卫生与预防医学,2017,28(1):116-117.
[14]来明月,王江宁,王宇.西双版纳州2010~2015年梅毒流行特征分析[J].皮肤病与性病,2016,38(6):431-434.
[15]高守芝,陈曦,贺健梅,等.湖南省部分医疗机构梅毒和淋病病例报告与诊断调查[J].实用预防医学,2011,18(10):1865-1867.
[16]陈晨春,唐咸艳.2008-2013年南宁市梅毒小尺度的时空聚集性研究[J].中国皮肤性病学杂志,2015,29(7):699-703.
[17]杨振,王念,王宇.中国性病疫情的时空差异与经济驱动机制--以淋病、梅毒为例[J].热带地理,2016,36(5):761-766.