2016年贵州省乙型病毒性肝炎空间聚集性分析
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摘要
目的应用空间自相关和空间扫描统计量分析2016年贵州省乙型病毒性肝炎发病的空间流行特征,探测其空间自相关性和聚集范围。方法运用Excel 2007整理贵州省88个县(区)乙肝发病率,应用Arc GIS 10. 2进行空间自相关分析及地图可视化表达;运用Sa TScan 9. 6探索乙肝发病聚集大小和范围。结果 2016年贵州省乙肝报告发病率50. 00/10万,乙肝发病率存在空间正自相关性(Moran's I值为0. 250 6,P<0. 01)。局部空间自相关性分析,2016年贵州省乙肝发病存在"High-High"、"Low-Low"的空间正相关(P<0. 05);"High-High"(热点)的区域为独山、锦屏、黎平、思南、德江县,"Low-Low"(冷点)区域为云岩区、南明区、观山湖区、水城县、六枝特区、长顺县。单纯空间扫描统计量显示乙肝发病具有4个可能聚集范围(P<0. 01),最大可能聚集区域有黔东南、黔南地区的独山、三都、榕江等16个县(区)。结论 2016年贵州省乙肝报告发病率具有空间聚集性,主要聚集在黔南、遵义、黔东南等3个州(市),独山、黎平、锦屏等3个县区,是贵州省乙肝防控重点区域。
Objective To analyze the spatial epidemiological characteristics of hepatitis B( HB) in Guizhou Province in 2016 and explore the spatial autocorrelation and aggregation scope by using spatial autocorrelation and spatial scan statistics. Methods The HB incidence of 88 counties( districts) of Guizhou was collected with Excel 2007,and the spatial autocorrelation analysis and map visualization were performed with ArcGIS 10. 2. The SaTScan 9. 6 was used to explore the aggregation size and scope of HB incidence. Results The incidence of HB reported in Guizhou in 2016 was 50. 00/105,which implicated the positive spatial autocorrelation( Moran's I value was 0. 250 6,P < 0. 01). Local spatial autocorrelation analysis showed that there was a positive spatial correlation model of HB in Guizhou in2016,the models were High-High and Low-Low( P < 0. 05). The area of "High-High"( hot spot)included Dushan,Jinping,Liping,Sinan and Dejiang county,and the "Low-Low"( cold spot) was Yunyan district,Nanming district,Guanshanhu district,Shuicheng county,Liuzhi district and Changshun county. Simple spatial scan statistics showed that there were 4 possible aggregation ranges of HB( P<0. 01),and the largest possible aggregation areas were 16 counties( districts) including Dushan,Sandu and Rongjiang in southeastern and southern of Guizhou. Conclusion In 2016,the HB incidence reported in Guizhou has spatial aggregation,mainly in three prefectures( cities) such as Qiannan,Zunyi,Qiandongnan,and three counties such as Dushang,Liping,Jingping,which are the focus of prevention and control of HB in Guizhou.
Objective To analyze the spatial epidemiological characteristics of hepatitis B( HB) in Guizhou Province in 2016 and explore the spatial autocorrelation and aggregation scope by using spatial autocorrelation and spatial scan statistics. Methods The HB incidence of 88 counties( districts) of Guizhou was collected with Excel 2007,and the spatial autocorrelation analysis and map visualization were performed with ArcGIS 10. 2. The SaTScan 9. 6 was used to explore the aggregation size and scope of HB incidence. Results The incidence of HB reported in Guizhou in 2016 was 50. 00/105,which implicated the positive spatial autocorrelation( Moran's I value was 0. 250 6,P < 0. 01). Local spatial autocorrelation analysis showed that there was a positive spatial correlation model of HB in Guizhou in2016,the models were High-High and Low-Low( P < 0. 05). The area of "High-High"( hot spot)included Dushan,Jinping,Liping,Sinan and Dejiang county,and the "Low-Low"( cold spot) was Yunyan district,Nanming district,Guanshanhu district,Shuicheng county,Liuzhi district and Changshun county. Simple spatial scan statistics showed that there were 4 possible aggregation ranges of HB( P<0. 01),and the largest possible aggregation areas were 16 counties( districts) including Dushan,Sandu and Rongjiang in southeastern and southern of Guizhou. Conclusion In 2016,the HB incidence reported in Guizhou has spatial aggregation,mainly in three prefectures( cities) such as Qiannan,Zunyi,Qiandongnan,and three counties such as Dushang,Liping,Jingping,which are the focus of prevention and control of HB in Guizhou.
引文
[1]张国民,缪宁,郑徽,等.中国2005-2016年乙型病毒性肝炎报告发病的年龄和地区特征[J].中国疫苗和免疫,2018,24(2):121-126.
[2]Zhiqiang G,Zhaohui D,Qinhuan W,et al.Cost of chronic hepatitis B infection in China[J].Journal of Clinical Gastroenterology,2004,38(10 Suppl 3):S175.
[3]周晓农.空间流行病学[M].北京:科学出版社,2009.
[4]唐咸艳,李峤,仇小强,等.扫描统计量中最大空间扫描窗口的尺度选择[J].中华疾病控制杂志,2015,19(3):316-320.
[5]张国民,缪宁,郑徽,等.中国2005-2016年乙型病毒性肝炎报告发病的年龄和地区特征[J].中国疫苗和免疫,2018,24(2):121-126.
[6]杨燕妮,陶沁,蒋琦,等.贵州省2004-2016年乙型病毒性肝炎病例监测情况分析[J].现代预防医学,2017,44(23):4365-4368.
[7]刘维量,寇增强,陈保立,等.山东省2014-2016年布鲁氏菌病空间分布特征和空间自相关分析[J].中华疾病控制杂志,2018,22(9):897-901.
[8]肖晓兰,左传田,赵杰,等.2003-2012年广西肝癌发病的时空趋势研究[J].中国卫生统计,2015,32(6):990-992.
[9]牟敬锋,赵星,樊静洁,等.2014-2016年深圳市空气污染时空分布特征[J].卫生研究,2018(2):270-276.
[10]魏娜娜,鲍俊哲,宇传华,等.中国卫生总费用空间分布特征与趋势分析[J].中国卫生资源,2016,19(1):47-51.
[11]宋全伟,李克莉,张国民,等.中国2005-2014年乙型病毒性肝炎空间流行病学特征分析[J].中国疫苗和免疫,2015(6):601-605.
[12]张嘉成,鲍倡俊,刘文东,等.江苏省病毒性乙型肝炎流行趋势GIS空间分析[J].中国卫生统计,2013,30(3):351-353.
[13]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.
[14]王玮,王建军,唐继海,等.安徽省2010-2015年麻疹时空分布特征探索[J].中国疫苗和免疫,2016(6):627-631.
[15]冯军,管庆虎,徐飞,等.2014年贵州省乙型病毒性肝炎空间分布特征分析[J].现代预防医学,2017,44(1):5-12.
[2]Zhiqiang G,Zhaohui D,Qinhuan W,et al.Cost of chronic hepatitis B infection in China[J].Journal of Clinical Gastroenterology,2004,38(10 Suppl 3):S175.
[3]周晓农.空间流行病学[M].北京:科学出版社,2009.
[4]唐咸艳,李峤,仇小强,等.扫描统计量中最大空间扫描窗口的尺度选择[J].中华疾病控制杂志,2015,19(3):316-320.
[5]张国民,缪宁,郑徽,等.中国2005-2016年乙型病毒性肝炎报告发病的年龄和地区特征[J].中国疫苗和免疫,2018,24(2):121-126.
[6]杨燕妮,陶沁,蒋琦,等.贵州省2004-2016年乙型病毒性肝炎病例监测情况分析[J].现代预防医学,2017,44(23):4365-4368.
[7]刘维量,寇增强,陈保立,等.山东省2014-2016年布鲁氏菌病空间分布特征和空间自相关分析[J].中华疾病控制杂志,2018,22(9):897-901.
[8]肖晓兰,左传田,赵杰,等.2003-2012年广西肝癌发病的时空趋势研究[J].中国卫生统计,2015,32(6):990-992.
[9]牟敬锋,赵星,樊静洁,等.2014-2016年深圳市空气污染时空分布特征[J].卫生研究,2018(2):270-276.
[10]魏娜娜,鲍俊哲,宇传华,等.中国卫生总费用空间分布特征与趋势分析[J].中国卫生资源,2016,19(1):47-51.
[11]宋全伟,李克莉,张国民,等.中国2005-2014年乙型病毒性肝炎空间流行病学特征分析[J].中国疫苗和免疫,2015(6):601-605.
[12]张嘉成,鲍倡俊,刘文东,等.江苏省病毒性乙型肝炎流行趋势GIS空间分析[J].中国卫生统计,2013,30(3):351-353.
[13]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.
[14]王玮,王建军,唐继海,等.安徽省2010-2015年麻疹时空分布特征探索[J].中国疫苗和免疫,2016(6):627-631.
[15]冯军,管庆虎,徐飞,等.2014年贵州省乙型病毒性肝炎空间分布特征分析[J].现代预防医学,2017,44(1):5-12.
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