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2014年-2016年宁波市食源性疾病暴发事件空间分布特征分析 被引量:7

Analysis of spatial distribution characteristics of food borne disease incidents in Ningbo during 2014-2016
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摘要 目的分析2014年-2016年宁波市食源性疾病暴发事件的空间分布特征,为各地今后开展事件防控措施提供针对性较强的理论依据。方法运用GIS技术描述2014年-2016年食源性疾病(食物中毒)报告系统上的食源性疾病事件空间分布特征。结果 2014年-2016年宁波市共上报食源性疾病事件45起,涉及病例477例,死亡1例;宁海县是宁波地区食源性疾病暴发事件较多地区,该地区事件主要场所是宾馆饭店和家庭,诱发食品主要是海产品和毒蘑菇,致病因素主要是副溶血性弧菌、组胺和蘑菇毒素;其他地区食源性疾病事件也呈现出一定的地区分布特点。结论 GIS技术能够比较直观形象的反映出空间分布特征;2014年-2016年宁波市食源性疾病暴发事件存在明显的空间分布特征,为制定有针对性的防控措施具有较强应用价值。 Objective To analyze the spatial distribution characteristics of food borne disease incidents in Ningbo during2014-2016,in order to provide solid targeted theoretical basis for carrying out events prevention and control measures.Methods To describe the spatial distribution characteristics of food borne disease incidents reported through the national reporting system for food borne disease(food poisoning) incidents in Ningbo during 2014-2016 by geographic information system(GIS). Results A total of 45 food borne disease incidents were reported in Ningbo during 2014-2016,involving 477 cases and 1 death; Ninghai county was a epidemic area of food borne disease outbreaks,mainly from seafood and poisonous mushrooms in hotels,restaurants and families. And the main pathogens were Vibrio parahaemolyticus,histamine and mushroom toxins; and food borne disease also showed certainly regional distribution in other places. Conclusion GIS can reflects the spatial distribution features intuitively and visually. It' s clear that the food borne disease outbreaks in Ningbo during 2014-2016 showed spatial distribution characteristics. It has a strong application value for the establishment of targeted prevention and control measures.
作者 张丹丹 郭延波 张琰 ZHANG Dan - dan;GUO Yan- bo;ZHANG Yan(Ningbo Municipal Center for Disease Control and Prevention, Ningbo, Zhejiang 315010, China)
出处 《中国卫生检验杂志》 CAS 2018年第12期1526-1528,1530,共4页 Chinese Journal of Health Laboratory Technology
关键词 食源性疾病事件 地理信息系统 空间分布 Food borne disease incidents Geographic information system Spatial distribution
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