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贝叶斯网络分析仔猪腹泻。

Bayesian Network analysis of piglet scours.

机构信息

Unaffiliated, Insch, Aberdeenshire, AB52 6UE, Scotland.

Sydney School of Veterinary Science, The University of Sydney, Camden, Australia.

出版信息

Sci Rep. 2017 Jul 24;7(1):6202. doi: 10.1038/s41598-017-06399-2.

DOI:10.1038/s41598-017-06399-2
PMID:28740158
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5524950/
Abstract

Diarrhoeal disease (scours) in piglets, often associated with enterotoxigenic Escherichia coli (ETEC), is a substantial financial burden to the pig industry worldwide. Previous research has not explicitly examined the relationships between farm, pen and microbiological factors. Here we present a state of the art analysis to reveal empirical indirect - as well as direct - associations between management factors as putative risks for scours in pre- and post-weaned piglets. A Bayesian Network is constructed to identify the optimal structural model describing the relationships between risk factors. An additive model is then built to estimate more epidemiologically familiar odds ratios. Farm-level variance dominates the model, making many pen-level associations null. However, there is evidence that pre-weaning scours are less likely on farms with <400 sows (0.14, 0.03-0.50). Our results strongly suggest that smaller production units (piglets/pen) could reduce the incidence of scours in piglets. There is also some evidence that ownership of other livestock is a potential risk factor for pre-weaning scours, although this was observed only at one farm. Future research should be directed at better understanding the role of herd size and investigating the relationship between managing other livestock and the occurrence of scours in pig herds.

摘要

仔猪腹泻病(腹泻),常与肠产毒性大肠杆菌(ETEC)有关,是全球养猪业的重大经济负担。以前的研究并未明确检查农场、猪圈和微生物因素之间的关系。在这里,我们进行了一项先进的分析,以揭示管理因素与断奶前和断奶后仔猪腹泻的潜在风险之间的经验间接和直接关联。构建了一个贝叶斯网络来识别描述风险因素之间关系的最优结构模型。然后构建了一个加性模型来估计更具流行病学意义的比值比。农场层面的方差占主导地位,使许多猪圈层面的关联变为无效。然而,有证据表明,母猪数量<400 的农场发生断奶前腹泻的可能性较小(0.14,0.03-0.50)。我们的结果强烈表明,较小的生产单位(每头猪/猪圈)可以降低仔猪腹泻的发病率。也有一些证据表明,饲养其他牲畜是断奶前腹泻的潜在风险因素,但仅在一个农场观察到这种情况。未来的研究应致力于更好地了解畜群规模的作用,并调查管理其他牲畜与猪群腹泻发生之间的关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96f4/5524950/1fc004ce494c/41598_2017_6399_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96f4/5524950/76edd214d452/41598_2017_6399_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96f4/5524950/1fc004ce494c/41598_2017_6399_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96f4/5524950/76edd214d452/41598_2017_6399_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96f4/5524950/1fc004ce494c/41598_2017_6399_Fig2_HTML.jpg

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Use of Bayesian Belief Network techniques to explore the interaction of biosecurity practices on the probability of porcine disease occurrence in Canada.运用贝叶斯信念网络技术探究加拿大生物安全措施之间的相互作用对猪病发生概率的影响。
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Modeling Dynamic Human Behavioral Changes in Animal Disease Models: Challenges and Opportunities for Addressing Bias.
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