本研究基于贝叶斯网络分析法建立了加拿大生物安全管理实践与猪场疾病发生的互作模型。该方法的优点是可以探索生物安全管理实践与猪场疾病发生率的互作关系及生物安全管理实践的相对重要性。研究建立了2010年加拿大218个商品猪场生物安全管理实践的数据库以及2010-2012年其中90个猪场疾病发生率及猪群健康状态数据库。模型考虑了4种疾病，分别是猪繁殖与呼吸综合征、猪流感、猪支原体肺炎和猪痢疾。模型结果表明，猪场疾病发生率受到一系列生物安全措施的显著影响。猪繁殖与呼吸综合症及支原体肺炎的发病率的升高与饲料洒落槽外不及时清理、粪污运到与猪场相邻的农场进行施肥等显著相关。猪流感及痢疾发病率的升高与猪场允许外来车辆不经清洁或消毒直接进入生产区有关。同时，出栏猪群健康状态未知时，也容易诱发猪痢疾感染。最后研究讨论了该模型用于评价加拿大生猪产业疾病风险评估并降低疾病发生率的可行性。
外文摘要：Identification and quantification of pathogen threats need to be a priority for the Canadian swine industry so that resources can be focused where they will be most effective. Here we create a tool based on a Bayesian Belief Network (BBN) to model the interaction between biosecurity practices and the probability of occurrence of four different diseases on Canadian swine farms. The benefits of using this novel approach, in comparison to other methods, is that it enables us to explore both the complex interaction and the relative importance of biosecurity practices on the probability of disease occurrence. In order to build the BBN we used two datasets. The first dataset detailed biosecurity practices employed on 218 commercial swine farms across Canada in 2010. The second dataset detailed animal health status and disease occurrence on 90 of those farms between 2010 and 2012. We used expert judgement to identify 15 biosecurity practices that were considered the most important in mitigating disease occurrence on farms. These included: proximity to other livestock holdings, the health status of purchased stock, manure disposal methods, as well as the procedures for admitting vehicles and staff. Four diseases were included in the BBN: Porcine reproductive and respiratory syndrome (PRRS), (a prevalent endemic aerosol pathogen), Swine influenza (SI) (a viral respiratory aerosol pathogen), Mycoplasma pneumonia (MP) (an endemic respiratory disease spread by close contact and aerosol) and Swine dysentery (SD) (an enteric disease which is re-emerging in North America). This model indicated that the probability of disease occurrence was influenced by a number of manageable biosecurity practices. Increased probability of PRRS and of MP were associated with spilt feed (feed that did not fall directly in a feeding trough), not being disposed of immediately and with manure being brought onto the farm premises and spread on land adjacent to the pigs. Increased probabilities of SI and SD were associated with the farm allowing access to visiting vehicles without cleaning or disinfection. SD was also more likely to occur when the health status of purchased stock was not known. Finally, we discuss how such a model can be used by the Canadian swine industry to quantify disease risks and to determine practices that may reduce the probability of disease occurrence.
外文关键词：Bayesian Belief Network；Disease probability；Swine farm；Biosecurity
作者：Cox R, Revie CW, Hurnik D等，
作者单位：加拿大爱德华王子岛大学。
期刊名称：PREVENTIVE VETERINARY MEDICINE
期刊影响因子：2.182
出版年份：2016
出版刊次：9
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