中国媒介生物学及控制杂志 ›› 2019, Vol. 30 ›› Issue (6): 634-638.DOI: 10.11853/j.issn.1003.8280.2019.06.009

• 论著 • 上一篇    下一篇

基于层次分析法的河北省病媒生物密度监测质量评价方法研究

马丽华, 黄钢, 王喜明   

  1. 河北省疾病预防控制中心有害生物防制所, 河北 石家庄 050021
  • 收稿日期:2019-09-05 出版日期:2019-12-20 发布日期:2019-12-20
  • 通讯作者: 黄钢,Email:bingmeicdc@126.com
  • 作者简介:马丽华,女,主管技师,主要从事病媒生物监测与分类研究,Email:malihua777@163.com
  • 基金资助:
    河北省医学科学研究重点课题(20150577)

A quality assessment method based on the analytic hierarchy process for vector density surveillance in Hebei province, China

MA Li-hua, HUANG Gang, WANG Xi-ming   

  1. Hebei Center for Disease Control and Prevention, Shijiazhuang 050021, Hebei Province, China
  • Received:2019-09-05 Online:2019-12-20 Published:2019-12-20
  • Supported by:
    Supported by the Key Issues of Medical Science Research in Hebei Province (No. 20150577)

摘要: 目的 应用层次分析法(AHP)计算河北省病媒生物密度监测工作质量评价指标权重,排序不同指标对监测质量的影响力。方法 以2014-2015年河北省市、县两级4种病媒生物密度监测和质控工作完成情况为参考,采用AHP法对评价指标构建判断矩阵,计算评价指标权重。结果 鼠类监测质量主要影响指标有监测点分布符合率、监测点选择符合率和标本种类符合率,权重分别为0.197 0、0.197 0和0.175 6;蚊类监测质量主要影响指标有监测时间符合率、监测点分布符合率、监测点选择符合率、标本数量符合率和标本种类符合率,权重分别为0.204 5、0.136 4、0.136 4、0.136 4和0.136 4;蝇类监测质量主要影响指标有标本种类符合率、监测点分布符合率和监测点选择符合率,权重分别为0.235 1、0.156 7和0.156 7;蜚蠊监测质量主要影响指标有标本数量符合率、监测点分布符合率和监测点选择符合率,权重分别为0.235 1、0.156 7和0.156 7。结论 AHP法可用于病媒生物密度监测质量评价,指标权重能够体现出不同指标在4种病媒生物密度监测工作中对质量影响的相对重要程度,可为做好病媒生物监测质控工作提供参考。

关键词: 层次分析法, 病媒生物密度监测, 质量评价, 权重

Abstract: Objective To calculate the weights of quality assessment indicators of vector density surveillance in Hebei province, China by the analytic hierarchy process (AHP), and to rank those indicators in the order of their influence on quality of surveillance. Methods Based on the achievement data on density surveillance and quality control of four vectors in both cities and counties of Hebei province from 2014 to 2015, AHP was applied to construct a judgment matrix and calculate the weights of assessment indicators. Results The main influencing indicators of quality of rodent surveillance were coincidence rate of distribution of surveillance points, coincidence rate of selection of surveillance points, and coincidence rate of species of specimens, with the weights of 0.197 0, 0.197 0, and 0.175 6, respectively. The main influencing indicators of quality of mosquito surveillance were coincidence rate of surveillance time, coincidence rate of distribution of surveillance points, coincidence rate of selection of surveillance points, coincidence rate of quantity of specimens, and coincidence rate of species of specimens, with the weights of 0.204 5, 0.136 4, 0.136 4, 0.136 4, and 0.136 4, respectively. The main influencing indicators of quality of fly surveillance were coincidence rate of species of specimens, coincidence rate of distribution of surveillance points, and coincidence rate of selection of surveillance points, with the weights of 0.235 1, 0.156 7, and 0.156 7, respectively. The main influencing indicators of quality of cockroach surveillance were coincidence rate of quantity of specimens, coincidence rate of distribution of surveillance points, and coincidence rate of selection of surveillance points, with the weights of 0.235 1, 0.156 7, and 0.156 7, respectively. Conclusion AHP can be used to assess the quality of vector density surveillance. The weights of indicators can reflect the relative importance of different indicators in the quality of density surveillance of four vectors. It can provide a reference for the quality control of vector density surveillance.

Key words: Analytic hierarchy process, Vector density surveillance, Quality assessment, Weight

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