• 论著 •

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

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)

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.