叶敏, 吴刚, 周炯林, 王采典, 黄雷, 胡荣星. 浙江省舟山口岸国际航行船舶医学媒介生物传入风险的logistic回归分析[J]. 疾病监测, 2017, 32(9): 789-792. DOI: 10.3784/j.issn.1003-9961.2017.09.019
引用本文: 叶敏, 吴刚, 周炯林, 王采典, 黄雷, 胡荣星. 浙江省舟山口岸国际航行船舶医学媒介生物传入风险的logistic回归分析[J]. 疾病监测, 2017, 32(9): 789-792. DOI: 10.3784/j.issn.1003-9961.2017.09.019
YE Min, WU Gang, ZHOU Jiong-lin, WANG Cai-dian, HUANG Lei, HU Rong-xin. Logistic regression analysis on risk factors associated with introduction of medical vectors by international navigation ships at Zhoushan port, Zhejiang[J]. Disease Surveillance, 2017, 32(9): 789-792. DOI: 10.3784/j.issn.1003-9961.2017.09.019
Citation: YE Min, WU Gang, ZHOU Jiong-lin, WANG Cai-dian, HUANG Lei, HU Rong-xin. Logistic regression analysis on risk factors associated with introduction of medical vectors by international navigation ships at Zhoushan port, Zhejiang[J]. Disease Surveillance, 2017, 32(9): 789-792. DOI: 10.3784/j.issn.1003-9961.2017.09.019

浙江省舟山口岸国际航行船舶医学媒介生物传入风险的logistic回归分析

Logistic regression analysis on risk factors associated with introduction of medical vectors by international navigation ships at Zhoushan port, Zhejiang

  • 摘要: 目的 探索国际航行船舶外来医学媒介生物传入的风险因素。方法 拟合舟山口岸2016年国际航行船舶数据,构建多因素非条件logistic回归模型,分析入境船舶携带媒介生物的风险因素。结果 2016年舟山口岸的入境船舶共计1 272艘,其中213艘船舶截获媒介生物,阳性检出率为16.75%。多因素分析显示:船舶类型(OR冷藏船vs.集装箱船=7.591;OR散杂货船vs.集装箱船=1.956;OR其他vs.集装箱船=3.658)、到达季节(OR夏季vs.冬季=3.677;OR春季vs.冬季=3.333;OR秋季vs.冬季=2.928)、船舶免予卫生控制证书签发港口(OR=1.689)、装载货物(OR=1.651)、来源地属传染病疫区(OR=1.596)、船龄(OR=1.023)等6项因素与船舶携带外来医学媒介生物存在关联(P 0.05)。结论 通过对医学媒介生物携带影响因素的量化分析,为国际航行船舶携带医学媒介生物风险评估及预警系统的建立提供理论基础,同时也利于确定重点检疫对象,指导实际检疫工作。

     

    Abstract: Objective To explore risk factors associated with introduction of medical vectors by international navigation ships. Methods Quarantine data for all ships arriving at Zhoushan port in 2016 were fitted with univariate and multivariate unconditional logistic regression model to identify the potential risk factors associated with introduction of medical vectors by international navigation ships. Results Medical vectors were captured in 213 of 1 272 ships arrived at Zhoushan port in 2016. The positive detection rate was 16.75%. Six risk factors identified by multivariate analysis were ship type (ORrefrigerated ship vs. container ship=7.591;ORcargo ship vs. container ship=1.956;ORother ship vs. container ship=3.658), arriving season (ORsummer vs.winter=3.677; ORspring vs.winter=3.333; ORautumn vs.winter=2.928), issuance port of ship sanitation control exemption certificate (SSCEC) (OR=1.689), cargo varieties (OR=1.651), coming from affected area (OR=1.596), ship age (OR=1.023). Conclusion Multivariate regression analysis on risk factors associated with introduction of medical vectors by international navigation ships can provide theoretic basis for the establishment of risk assessment and early warning system and guide quarantine practice through identifying ships with high risk of carrying medical vectors.

     

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