论著

四川省石渠县棘球蚴病流行的影响因素分析

  • 何伟 ,
  • 王谦 ,
  • 黄燕 ,
  • 喻文杰 ,
  • 张光葭 ,
  • 廖沙 ,
  • 王奇 ,
  • 杨柳 ,
  • 陈凡 ,
  • 李汭芮 ,
  • 钟波
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  • 四川省疾病预防控制中心寄生虫病预防控制所,成都 610041

作者简介:何伟(1986-),男,硕士,公卫医师,从事棘球蚴病预防控制研究。E-mail:sccdchewei@163.com

收稿日期: 2019-01-09

  网络出版日期: 2019-09-05

基金资助

四川省科技计划项目(No. 2018SZ0116)

Risk factors of echinococcosis in Shiqu County, Sichuan Province

  • Wei HE ,
  • Qian WANG ,
  • Yan HUANG ,
  • Wen-jie YU ,
  • Guang-jia ZHANG ,
  • Sha LIAO ,
  • Qi WANG ,
  • Liu YANG ,
  • Fan CHEN ,
  • Rui-rui LI ,
  • Bo ZHONG
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  • Institute of Parasitic Disease, Sichuan Center for Disease Control and Prevention, Chengdu 610041, China

Received date: 2019-01-09

  Online published: 2019-09-05

Supported by

Supported by the Sichuan Science and Technology Program(No. 2018SZ0116)

摘要

目的 探索人群棘球蚴病流行的主要影响因素,研究棘球蚴病的流行与多种影响因素的关系,为开展棘球蚴病防治工作和制定适合本地区的控制策略和措施提供依据。方法 从2015年11月-2017年6月在四川省石渠县开展的棘球蚴病流行情况调查的数据中提取对棘球蚴病流行可能有影响的因素作为自变量,以人群患病率作为因变量,进行直线回归分析,筛选出有统计学意义的因素,进行多重线性回归分析,建立多重线性回归模型。结果 单因素线性回归分析结果显示,户均犬数、犬感染率、户均羊数、户均牛数、牛患病率、年户均自宰牛羊数、小型哺乳类动物密度、防治棘球蚴病知识知晓率均是人群患病的影响因素(P < 0.05),回归系数分别为 5.278、0.818、0.183、0.274、0.234、3.035、0.038、-0.539,其中户均犬数的影响最大,户均犬数每增加1条犬,人群患病率增加5.278倍。多重线性回归分析结果显示,防治知识知晓率(X9)、户均犬数(X1)、犬感染率(X2)和小型哺乳类动物密度(X7)对人群患病率的影响有统计学意义(P < 0.05),多重线性回归模型方程为Y = 11.213 - 0.146X9 + 2.184X1 + 0.231X2 + 0.009X7。其中,户均犬数对人群患病率的影响最大。结论 户均犬数、犬感染率、小型哺乳类动物密度、防治棘球蚴病知识知晓率等因素与人群患棘球蚴病有关。

本文引用格式

何伟 , 王谦 , 黄燕 , 喻文杰 , 张光葭 , 廖沙 , 王奇 , 杨柳 , 陈凡 , 李汭芮 , 钟波 . 四川省石渠县棘球蚴病流行的影响因素分析[J]. 中国寄生虫学与寄生虫病杂志, 2019 , 37(4) : 428 -432 . DOI: 10.12140/j.issn.1000-7423.2019.04.010

Abstract

Objective To analyze the main influencing and risk factors related to the epidemic of human echinococcosis and their impacts on the prevalence of echinococcosis as a basis for providing a strategy for the better control of echinococcosis in the region. Methods The data of an epidemiological survey on echinococcosis in Shiqu, Sichuan, from November 2015 to June 2017 were collected to identify the factors related to the endemic of echinococcosis as independent variables, and the population prevalence of echinococcosis as dependent variables. Linear regression analysis was conducted to identify the factors with statistical significance related to the endemic of echinococcosis. A multiple linear regression model was established to analyze the factors that significantly effect the prevalence of echinococcosis in the region. Results The results of single factor linear regression analysis showed that the average number of dog per household, the infection rate of dogs, the average number of sheep per household, the average number of cattle per household, the prevalence rate of cattle, the average slaughtered number of cattle and sheep per household, the density of small mammals, and people’s awareness for the knowledge to prevent and control echinococcosis were all the influencing and risk factors (with b = 5.278, 0.818, 0.183, 0.274, 0.234, 3.035, 0.038, -0.539, respectively, P < 0.05). The average number of dog per household has the greatest impact. The prevalence rate of the population could increases by 5.278 times if one dog would be increased in each household. The results of multiple linear regression analysis showed that the knowledge awareness(X9), the average number of dog per household (X1), the infection rate of dogs (X2) and the density of small mammals (X7) had significant effect on the prevalence of echinococcosis in local population(P < 0.05). The equation of multiple linear regression model was Y = 11.213 - 0.146X9 + 2.184X1 + 0.231X2 + 0.009X7. Among them, the average number of dogs per household has the greatest impact. Conclusion The effective and risk factors such as the number of dog per household, the rate of canine infection, the density of small mammals, and the awareness rate of prevention and treatment of echinococcosis are related to the prevalence of echinococcosis in the endemic area.

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