Objective To understand the spatial distribution and epidemic characteristics of current cases of schistosomiasis in Anqing City and guide the prevention and control of schistosomiasis. Methods The information of schistosomiasis cases in Anqing City was collected,and the spatial database of township level was established.Through descriptive statistical analysis and spatial statistical analysis,the spatial distribution and epidemic characteristics of schistosomiasis cases in Anqing City were expounded. Results A total of 9 922 cases of schistosomiasis were reported,including 8 133 cases of chronic schistosomiasis and 1 789 cases of advanced schistosomiasis.The occupation of chronic and advanced schistosomiasis cases were mainly farmers,accounting for 92.82% (7 549 / 8 133) and 92.57% (1 656 / 1 789),respectively.Global autocorrelation analysis showed that there was a spatial autocorrelation in the prevalence of chronic schistosomiasis (Moran's I=0.3088,Z=6.8534,P<0.01),and in the prevalence of advanced schistosomiasis (Moran's I=0.2446,Z=6.9193,P<0.01).The results of local autocorrelation analysis showed that the areas with high prevalence of chronic and advanced schistosomiasis were in the towns around Daguan District of the Yangtze River,Qili Lake and Wanhe river system,and the areas with high prevalence of chronic schistosomiasis were larger than those with high prevalence of advanced schistosomiasis. Conclusion There were positive spatial autocorrelation and local spatial aggregation in the distribution of chronic and advanced schistosomiasis cases in Anqing City.Prevention and control should be focused on the areas with high prevalence of schistosomiasis.
Key words
Schistosomiasis /
Spatial autocorrelation analysis /
Geographic information system /
Spatial distribution /
Spatial statistics
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
References
[1] 许静,吕山,曹淳力,等.我国血吸虫病消除工作进展及面临的挑战[J].中国血吸虫病防治杂志,2018,30(6):605-609.
[2] 周晓农,李石柱,洪青标,等.不忘初心送瘟神 科学防治谱新篇——纪念毛泽东主席《七律二首·送瘟神》发表60周年[J].中国血吸虫病防治杂志,2018,30(1):1-4.
[3] 周晓农.开展精准防治 实现消除血吸虫病的目标[J].中国血吸虫病防治杂志,2016,28(1):1-4.
[4] 姚金付,丁平,王桂芬.安庆市2005~2017年血吸虫病疫情分析[J].安徽预防医学杂志,2018,24(6):407-410,434.
[5] 徐珏.应用Moran'sⅠ系数分析杭州市手足口病的空间自相关性[D].杭州:浙江大学,2014.
[6] 姚保栋,周艺彪,王增亮,等.基于行政村尺度的安乡县晚期血吸虫病空间分布特征研究[J].中国血吸虫病防治杂志,2012,24(1):72-75.
[7] 饶华祥.基于时空聚集面板模型的肺结核病高危区域探测及影响因素研究[D].太原:山西医科大学,2017.
[8] 田鑫.吉林省2013~2016年麻疹空间分布特点分析[D].长春:吉林大学,2017.
[9] 陈艳艳.湖北省血吸虫病空间流行特征及预测分析[D].武汉:华中科技大学,2014.
[10] 高风华,何家昶,汪天平,等.安徽省预防控制血吸虫病中长期规划纲要(2004-2015年)终期评估报告[J].热带病与寄生虫学,2017,15(2):63-67.
[11] 何结宝,董红星.以控制传染源为主的血吸虫病综合防治策略效果评价[J].安徽预防医学杂志,2010,16(4):269,303.
[12] 汪子栋.安徽省血防林工程建设及综合效益评价[D].合肥:安徽农业大学,2014.
[13] 罗伟,肖瑛,周学文,等.2005~2014年血吸虫病门诊就诊者IHA检测结果分析[J].中国血吸虫病防治杂志,2016,28(1):92-93,96.
[14] 刘兆春,肖水源,周杰,等.2012年湖南省晚期血吸虫病流行病学特征分析[J].中国血吸虫病防治杂志,2014,26(2):148-152.
[15] 魏珊.我国乙类法定报告传染病的发病趋势和季节性研究[D].上海:复旦大学,2013.
[16] 汪天平.人兽共患寄生虫病的流行与防控[J].中国寄生虫学与寄生虫病杂志,2015,33(6):472-476.
[17] 徐俊芳,许静,杨国静,等.长江中游湖沼型地区血吸虫病流行影响因素分析[J].中国血吸虫病防治杂志,2011,23(6):634-641.
[18] 李伊婷.中国晚期血吸虫病疾病负担研究[D].北京:中国疾病预防控制中心,2019.
[19] 孙瑜,许大兵,张可可.728例晚期血吸虫病例分析[J].安徽预防医学杂志,2011,17(2):132.
[20] 周晓农,孙乐平,姜庆五,等.全国血吸虫病流行状况的地理信息系统空间分析[J].中华流行病学杂志,2000(4):21-23,81.
[21] 郝瑜婉,高风华,薛靖波,等.2004~2015年云南省血吸虫病传播风险时空聚集性分析[J].中国血吸虫病防治杂志,2019,31(3):269-274,279.