陕西省奶山羊重点养殖县区布鲁氏菌感染情况及其影响因素的横断面研究
A cross-sectional study of Brucella infection and its influencing factors in key breeding counties of dairy goats in Shaanxi Province
杨文欢 1赵光明 2赵仙苗 2焦韵洁 2王桂花 3游建华 2史冰君 2王青杰 2杨增岐 4赵合平2
作者信息
- 1. 西北农林科技大学动物医学院,陕西杨凌 712100;陕西省动物疫病预防控制中心,陕西西安 710016
- 2. 陕西省动物疫病预防控制中心,陕西西安 710016
- 3. 渭南市动物疫病预防控制中心,陕西渭南 714099
- 4. 西北农林科技大学动物医学院,陕西杨凌 712100
- 折叠
摘要
为掌握陕西省奶山羊布鲁氏菌的感染情况及其影响因素,本研究在陕西省6个奶山羊重点养殖县区813个奶山羊养殖单元采集22.87万份血清样品,采用虎红平板凝集试验(初筛试验)和试管凝集试验(确诊试验)检测,对其中286个奶山羊养殖场(户)开展现场问卷调查,并采用单因素分析和多因素logistic回归分析,确定布鲁氏菌的感染情况及其关联因素.结果显示,6个县区奶山羊布鲁氏菌个体感染率和群体感染率分别为0.02％和2.2％;4个检出布鲁氏菌抗体阳性的县区个体感染率介于0.02％～0.8％,群体感染率介于3.1％～6.5％,陈仓区、凤翔区分别与阎良区、富平县个体感染率存在统计学差异(P＜0.05),4个县区群体感染率间无统计学差异(P＞0.05);规模场与散养村个体感染率和群体感染率均存在统计学差异(P＜0.05).饮用河水、母羊有流产史、断奶羔羊存活率低于85％和本场人员兼职从事羊的屠宰贩卖等相关工作,这4个因素为奶山羊感染布鲁氏菌的潜在风险因素(P＜0.05);引入羊的检疫、入场车辆消毒为保护性因素(P＜0.05).多因素logistic回归方程为Logit[P(Y=1)]=-4.484+0.874X1+1.829X2-2.45 3X3+4.48 8X4-0.09X5+2.1X6-2.611X7+2.978X8,可用于奶山羊感染布鲁氏菌的风险预测.本研究结果提示,陇县、千阳县应重点加强调引入羊的检疫和落地监管,定期对高风险因素和动物进行监测,其余4个县区可以采取相同的布鲁氏菌病监测与净化策略,对布鲁氏菌阳性奶山羊群开展全群检测,重点开展奶山羊散养村的布鲁氏菌病监测净化工作;奶山羊养殖场(户)应重点关注人员车辆入场、饮水等高风险因素,做好引进羊的检疫,提高饲养管理能力和生物安全管理水平,才能有效降低布鲁氏菌的感染风险.本研究采用横断面研究方法调查了陕西省奶山羊重点养殖县区布鲁氏菌的感染率及其感染因素,为陕西省布鲁氏菌病的防控提供参考依据.
Abstract
In order to estimate the prevalence of brucellosis in dairy goats in Shaanxi Province and to identify the potential risk factors for brucellosis infection on farms,228700 serum samples were collected from 813 dairy goat breeding units in 6 counties of Shaanxi Province.Rose Bengal Test(screening test)and Serum Agglutination Test(confirmatory test)were used for detection.Additionally,questionnaire surveys were conducted among 286 dairy goat breeding household.The infection status of Brucella and potential associated factors were determined via univariate and multivariate logistic regression analysis.The results showed that the individual and herd infection rates of brucellosis in dairy goats were 0.02％and 2.2％,respectively.The individual infection rates detected by brucella antibody in 4 counties ranged from 0.02％to 0.8％,and the herd infection rates ranged from 3.1％to 6.5％.There were statistically significant differences in the individual infection rates between Chencang District,Fengxiang Distrist and Yanliang District,Fuping County,respectively(P＜0.05),while there were no statistically differences in the herd infection rates among the 4 counties(P＞0.05).Drinking river water,a history of ewe abortion,lamb survival rate below 85％after weaning,and personnel engaging in slaughter and sales of sheep as secondary work were identified as potential risk factors for Brucella infection in dairy goat farms/households(P＜0.05).Introducing quarantine before importing of goats and disinfecting vehicles before entering the farm were identified as protective factors(P＜0.05).Multi-factor logistic regression equation:Logit[P(Y=1)]=-4.484+0.874X1+1.829X2-2.453X3+4.488X4-0.09X5+2.1X6-2.611X7+2.978X8 can be used to predict the risk of brucella infection in dairy goat farms.The results suggest that Longxian County and Qianyang County should focus on strengthening quarantine and supervision for transferred(incoming)goats,and conducting regularly monitoring high-risk processes and animals.Other four counties can use the same brucellosis monitoring and purification strategies,conducting whole-group testing for positive herds,and focusing on brucellosis monitoring and purification of dairy goats in breeding villages.Dairy goat farmers should pay attention to high-risk processes such as personnel and vehicle entry,water consumption,and improve quarantine measures for incoming goats,improve feeding management ability and biosecurity management levels,and effectively reduce the risk of brucellosis infection.This study provides a reference for the prevention and control of brucellosis in Shaanxi Province.
关键词
布鲁氏菌病/奶山羊/横断面研究/风险因素分析Key words
brucellosis/dairy goats/cross-sectional study/risk factors analysis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据