2014-2016年我国三峡地区细菌性痢疾发病时空特征分析
|
摘要
目的了解我国三峡地区2014-2016年细菌性痢疾(菌痢)发病的时空分布特征,为影响因素分析和防控提供依据。方法 2014-2016年三峡地区菌痢报告病例数据和菌痢突发事件资料分别来源于"传染病报告信息管理系统"和"突发公共卫生事件报告管理系统",采用Geo Da 1.8.16.4软件进行全局和局部空间自相关分析,Sa TScan 9.4软件进行时空扫描统计分析,利用Arc GIS 10.3实现结果三维可视化。结果 2014-2016年,三峡地区菌痢报告发病率依次为24.00/10万、22.14/10万和20.84/10万,呈下降趋势。仅重庆市城口县报告一起菌痢暴发疫情,罹患率为5.36%(70/1 305)。全局空间自相关表明,三峡地区菌痢报告发病率整体上具有空间自相关性(Moran's I依次为0.194、0.227和0.482,P=0.001);局部空间自相关显示,2014-2016年菌痢发病热点县(区)个数分别为2、5和8个;冷点县(区)范围变化不大,依次为6、6和8个。逐年时空扫描分析发现,一类聚集区的聚集时间为每年的5-10月,且位置较稳定,均覆盖重庆西南部的渝中、大渡口、江北、沙坪坝、九龙坡、南岸、北碚、渝北、巴南和长寿共10个县(区),此外2014年和2015年还包含璧山区,2016年包含合川区;2014-2016年依次有4、3和5个二类聚集区,持续存在的是重庆市东北部的城口县和宜昌市中部的西陵区和伍家岗区。结论三峡地区菌痢报告发病率在县(区)水平上存在时空聚集性,重庆市主城区及其周边县(区)为高发聚集区,空间分析方法可以较好地应用于菌痢的时空聚集性分析,为菌痢防控提供参考依据。
Objective To investigate the spatial and temporal distribution of bacillary dysentery in the three gorges area from2014 to2016,and provide evidence for both further investigation of risk factors and interventions. Methods The incidence and outbreak data of bacillary dysentery in the three gorges area from2014 to2016 were obtained from National Notifiable Infectious Disease Reporting System and National Public Health Emergency Reporting Information System. The spatial autocorrelation analysis and spatial-temporal scan statistic were conducted by using software Geo Da1.8.16.4 and Sa TScan9.4 respectively. The results were visualized by using software Arc GIS10.3. Results The reported annual incidences of bacillary dysentery in the three gorges area from2014 to2016 were24.00/100 000,22.14/100 000 and20.84/100 000 respectively,showing a decrease trend. Only1 bacillary dysentery outbreak was reported in Chengkou county in the northeast of Chongqing and the attack rate was5.36%(70/1 305). Global spatial autocorrelation indicated that there was a spatial clustering in the incidence of bacillary dysentery(In turn,Moran's I coefficient is0.194,0.227,0.482,and P=0.001). Local spatial autocorrelation showed that the number of hot spot areas was2,5 and8 during2014-2016 respectively. The number of cold spot areas had slight change,which was6,6 and8 during2014-2016 respectively. Spatialtemporal scan statistic analysis found that the clustering period was during May-October in classⅠcluster areas steadily found in southwest Chongqing,including Yuzhong,Dadukou,Jiangbei,Shapingba,Jiulongpo,Nanan,Beibei,Yubei,Banan districts and Changshou county. Bishan county was included in2014 and2015,and Hechuan district was included in2016. A total of4,3 and5 classⅡcluster areas were found from2014 to2016 respectively,including Chengkou county of Chongqing,Xiling and Wujiagang districts of central Yichang all the time. Conclusion The incidence of bacillary dysentery had spatial and temporal clustering at county level in the three gorges area,and the areas with high incidences were the urban area of Chongqing and its surrounding counties. Spatial statistical analysis is suitable for the analysis of the spatial and temporal clusters of bacillary dysentery and can provide useful information for the disease prevention and control in the future.
Objective To investigate the spatial and temporal distribution of bacillary dysentery in the three gorges area from2014 to2016,and provide evidence for both further investigation of risk factors and interventions. Methods The incidence and outbreak data of bacillary dysentery in the three gorges area from2014 to2016 were obtained from National Notifiable Infectious Disease Reporting System and National Public Health Emergency Reporting Information System. The spatial autocorrelation analysis and spatial-temporal scan statistic were conducted by using software Geo Da1.8.16.4 and Sa TScan9.4 respectively. The results were visualized by using software Arc GIS10.3. Results The reported annual incidences of bacillary dysentery in the three gorges area from2014 to2016 were24.00/100 000,22.14/100 000 and20.84/100 000 respectively,showing a decrease trend. Only1 bacillary dysentery outbreak was reported in Chengkou county in the northeast of Chongqing and the attack rate was5.36%(70/1 305). Global spatial autocorrelation indicated that there was a spatial clustering in the incidence of bacillary dysentery(In turn,Moran's I coefficient is0.194,0.227,0.482,and P=0.001). Local spatial autocorrelation showed that the number of hot spot areas was2,5 and8 during2014-2016 respectively. The number of cold spot areas had slight change,which was6,6 and8 during2014-2016 respectively. Spatialtemporal scan statistic analysis found that the clustering period was during May-October in classⅠcluster areas steadily found in southwest Chongqing,including Yuzhong,Dadukou,Jiangbei,Shapingba,Jiulongpo,Nanan,Beibei,Yubei,Banan districts and Changshou county. Bishan county was included in2014 and2015,and Hechuan district was included in2016. A total of4,3 and5 classⅡcluster areas were found from2014 to2016 respectively,including Chengkou county of Chongqing,Xiling and Wujiagang districts of central Yichang all the time. Conclusion The incidence of bacillary dysentery had spatial and temporal clustering at county level in the three gorges area,and the areas with high incidences were the urban area of Chongqing and its surrounding counties. Spatial statistical analysis is suitable for the analysis of the spatial and temporal clusters of bacillary dysentery and can provide useful information for the disease prevention and control in the future.
引文
[1]刘海霞,孟蕾,刘东鹏,等.空间数据分析在甘肃省细菌性痢疾空间聚集性研究中的应用[J].疾病监测,2015,30(5):415-419.DOI:10.3784/j.issn.1003-9961.2015.05.019.Liu HX,Meng L,Liu DP,et al.Application of spatial data analysis on clustering of bacillary dysentery in Gansu[J].Dis Surveill,2015,30(5):415-419.DOI:10.3784/j.issn.1003-9961.2015.05.019.
[2]查文婷,郑剑,刘意,等.基于GIS技术2013年湖南省细菌性痢疾自相关和趋势面分析[J].中华疾病控制杂志,2015,19(11):1096-1100.DOI:10.16462/j.cnki.zhjbkz.2015.11.005.Zha WT,Zheng J,Liu Y,et al.Spatial autocorrelation and trend surface analysis of bacillary dysentery by geographic information system(GIS)in Hunan province in 2013[J].Chin J Dis Control Prev,2015,19(11):1096-1100.DOI:10.16462/j.cnki.zhjbkz.2015.11.005.
[3]李孟磊,黄丽莉,郭振平,等.细菌性痢疾临床诊断与病原学诊断符合率研究[J].当代医学,2012,18(14):158-159.DOI:10.3969/j.issn.1009-4393.2012.14.112.Li ML,Huang LL,Guo ZP,et al.Study on the Coincidence rate of the clinical diagnosis and etiological diagnosis of bacillary dysentery patients[J].Contemp Med,2012,18(14):158-159.DOI:10.3969/j.issn.1009-4393.2012.14.112.
[4]钟豪杰,常昭瑞,张静.中国2007年细菌性痢疾监测分析[J].中华流行病学杂志,2010,31(3):304-307.DOI:10.3760/cma.j.issn.0254-6450.2010.03.016.Zhong HJ,Chang ZR,Zhang J.Analysis on bacillary dysentery surveillance data collected from the National Surveillance System in 2007[J].Chin J Epidemiol,2010,31(3):304-307.DOI:10.3760/cma.j.issn.0254-6450.2010.03.016.
[5]姜庆五,赵飞.空间自相关分析方法在流行病学中的应用[J].中华流行病学杂志,2011,32(6):539-546.DOI:10.3760/cma.j.issn.0254-6450.2011.06.002.Jiang QW,Zhao F.Application of spatial autocorrelation method in epidemiology[J].Chin J Epidemiol,2011,32(6):539-546.DOI:10.3760/cma.j.issn.0254-6450.2011.06.002.
[6]Anselin L.How(not)to lie with spatial statistics[J].Am J Prev Med,2006,30 Suppl 2:S3-6.DOI:10.1016/j.amepre.2005.09.015.
[7]王远飞,何洪林.空间数据分析方法[M].北京:科学出版社,2007.Wang YF,He HL.Methods of spatial data analysis[M].Beijing:Science Press,2007.
[8]Anselin L.Local indicators of spatial association-LISA[J].Geogr Anal,1995,27(2):93-115.DOI:10.1111/j.1538-4632.1995.tb00338.x.
[9]Kulldorff M.A spatial scan statistic[J].Commun Stat Theory Methods,1997,26(6):1481-1496.DOI:10.1080/03610929708831995.
[10]Kulldorff M,Athas WF,Feurer EJ,et al.Evaluating cluster alarms:a space-time scan statistic and brain cancer in Los Alamos,New Mexico[J].Am J Public Health,1998,88(9):1377-1380.DOI:10.2105/AJPH.88.9.1377.
[11]Deng T,Huang Y,Yu SC,et al.Spatial-temporal clusters and risk factors of hand,foot,and mouth disease at the district level in Guangdong province,China[J].PLo S One,2013,8(2):e56943.DOI:10.1371/journal.pone.0056943.
[12]Lawson AB.Statistical methods in spatial epidemiology[M].2nd ed.New York:John Wiley&Sons,2006:111-115.
[13]李晓松,冯子健,殷菲,等.传染病时空聚集性探测与预测预警方法[M].北京:高等教育出版社,2014:261-285.Li XS,Feng ZJ,Yin F,et al.Spatio-temporal cluster detection,forecasting and early warning for infectious disease[M].Beijing:Higher Education Press,2014:261-285.
[14]肖辉,肖革新.时空扫描统计量在细菌性痢疾监测数据分析中的应用[J].中国食品卫生杂志,2014,26(1):83-87.DOI:10.13590/j.cjfh.2014.01.025.Xiao H,Xiao GX.Application of space-time permutation scan statistics inbacillary dysentery surveillance[J].Chin J Food Hyg,2014,26(1):83-87.DOI:10.13590/j.cjfh.2014.01.025.
[15]Xiao GX,Xu CD,Wang JF,et al.Spatial-temporal pattern and risk factor analysis of bacillary dysentery in the Beijing-TianjinTangshan urban region of China[J].BMC Public Health,2014,14:998.DOI:10.1186/1471-2458-14-998.
[16]蒋仁保,高慎男.菌痢报告发病率农村低于城市问题分析[J].现代预防医学,2007,34(24):4733-4734.DOI:10.3969/j.issn.1003-8507.2007.24.061.Jiang RB,Gao SN.The analysis of the incidence of bacillary dysentery in rural areas is lower than that in cities[J].Mod Prev Med,2007,34(24):4733-4734.DOI:10.3969/j.issn.1003-8507.2007.24.061.
[17]Nie CJ,Li HR,Yang LS,et al.Socio-economic factors of bacillary dysentery based on spatial correlation analysis in Guangxi,China[J].PLo S One,2014,9(7):e102020.DOI:10.1371/journal.pone.0102020.
[18]Li ZJ,Wang LG,Sun WG,et al.Identifying high-risk areas of bacillary dysentery and associated meteorological factors in Wuhan,China[J].Sci Rep,2013,3:3239.DOI:10.1038/srep03239.
[2]查文婷,郑剑,刘意,等.基于GIS技术2013年湖南省细菌性痢疾自相关和趋势面分析[J].中华疾病控制杂志,2015,19(11):1096-1100.DOI:10.16462/j.cnki.zhjbkz.2015.11.005.Zha WT,Zheng J,Liu Y,et al.Spatial autocorrelation and trend surface analysis of bacillary dysentery by geographic information system(GIS)in Hunan province in 2013[J].Chin J Dis Control Prev,2015,19(11):1096-1100.DOI:10.16462/j.cnki.zhjbkz.2015.11.005.
[3]李孟磊,黄丽莉,郭振平,等.细菌性痢疾临床诊断与病原学诊断符合率研究[J].当代医学,2012,18(14):158-159.DOI:10.3969/j.issn.1009-4393.2012.14.112.Li ML,Huang LL,Guo ZP,et al.Study on the Coincidence rate of the clinical diagnosis and etiological diagnosis of bacillary dysentery patients[J].Contemp Med,2012,18(14):158-159.DOI:10.3969/j.issn.1009-4393.2012.14.112.
[4]钟豪杰,常昭瑞,张静.中国2007年细菌性痢疾监测分析[J].中华流行病学杂志,2010,31(3):304-307.DOI:10.3760/cma.j.issn.0254-6450.2010.03.016.Zhong HJ,Chang ZR,Zhang J.Analysis on bacillary dysentery surveillance data collected from the National Surveillance System in 2007[J].Chin J Epidemiol,2010,31(3):304-307.DOI:10.3760/cma.j.issn.0254-6450.2010.03.016.
[5]姜庆五,赵飞.空间自相关分析方法在流行病学中的应用[J].中华流行病学杂志,2011,32(6):539-546.DOI:10.3760/cma.j.issn.0254-6450.2011.06.002.Jiang QW,Zhao F.Application of spatial autocorrelation method in epidemiology[J].Chin J Epidemiol,2011,32(6):539-546.DOI:10.3760/cma.j.issn.0254-6450.2011.06.002.
[6]Anselin L.How(not)to lie with spatial statistics[J].Am J Prev Med,2006,30 Suppl 2:S3-6.DOI:10.1016/j.amepre.2005.09.015.
[7]王远飞,何洪林.空间数据分析方法[M].北京:科学出版社,2007.Wang YF,He HL.Methods of spatial data analysis[M].Beijing:Science Press,2007.
[8]Anselin L.Local indicators of spatial association-LISA[J].Geogr Anal,1995,27(2):93-115.DOI:10.1111/j.1538-4632.1995.tb00338.x.
[9]Kulldorff M.A spatial scan statistic[J].Commun Stat Theory Methods,1997,26(6):1481-1496.DOI:10.1080/03610929708831995.
[10]Kulldorff M,Athas WF,Feurer EJ,et al.Evaluating cluster alarms:a space-time scan statistic and brain cancer in Los Alamos,New Mexico[J].Am J Public Health,1998,88(9):1377-1380.DOI:10.2105/AJPH.88.9.1377.
[11]Deng T,Huang Y,Yu SC,et al.Spatial-temporal clusters and risk factors of hand,foot,and mouth disease at the district level in Guangdong province,China[J].PLo S One,2013,8(2):e56943.DOI:10.1371/journal.pone.0056943.
[12]Lawson AB.Statistical methods in spatial epidemiology[M].2nd ed.New York:John Wiley&Sons,2006:111-115.
[13]李晓松,冯子健,殷菲,等.传染病时空聚集性探测与预测预警方法[M].北京:高等教育出版社,2014:261-285.Li XS,Feng ZJ,Yin F,et al.Spatio-temporal cluster detection,forecasting and early warning for infectious disease[M].Beijing:Higher Education Press,2014:261-285.
[14]肖辉,肖革新.时空扫描统计量在细菌性痢疾监测数据分析中的应用[J].中国食品卫生杂志,2014,26(1):83-87.DOI:10.13590/j.cjfh.2014.01.025.Xiao H,Xiao GX.Application of space-time permutation scan statistics inbacillary dysentery surveillance[J].Chin J Food Hyg,2014,26(1):83-87.DOI:10.13590/j.cjfh.2014.01.025.
[15]Xiao GX,Xu CD,Wang JF,et al.Spatial-temporal pattern and risk factor analysis of bacillary dysentery in the Beijing-TianjinTangshan urban region of China[J].BMC Public Health,2014,14:998.DOI:10.1186/1471-2458-14-998.
[16]蒋仁保,高慎男.菌痢报告发病率农村低于城市问题分析[J].现代预防医学,2007,34(24):4733-4734.DOI:10.3969/j.issn.1003-8507.2007.24.061.Jiang RB,Gao SN.The analysis of the incidence of bacillary dysentery in rural areas is lower than that in cities[J].Mod Prev Med,2007,34(24):4733-4734.DOI:10.3969/j.issn.1003-8507.2007.24.061.
[17]Nie CJ,Li HR,Yang LS,et al.Socio-economic factors of bacillary dysentery based on spatial correlation analysis in Guangxi,China[J].PLo S One,2014,9(7):e102020.DOI:10.1371/journal.pone.0102020.
[18]Li ZJ,Wang LG,Sun WG,et al.Identifying high-risk areas of bacillary dysentery and associated meteorological factors in Wuhan,China[J].Sci Rep,2013,3:3239.DOI:10.1038/srep03239.