| 基于抗体筛查的美国猪群流行性腹泻病毒真流行率分布推断 |
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| 引用本文： | 张志诚,陈梅娟,艾军.基于抗体筛查的美国猪群流行性腹泻病毒真流行率分布推断[J].畜牧兽医学报,2021,52(7):2013-2024. |
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| 作者姓名： | 张志诚 陈梅娟 艾军 |
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| 作者单位： | 1. 中国动物卫生与流行病学中心, 国家非洲猪瘟参考实验室, 青岛 266032;2. 宁夏大学农学院, 银川 750000;3. 昆明海关技术中心, 昆明 650228 |
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| 基金项目： | “十三五”国家重点研发计划（2016YFD0501104） |
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| 摘 要： | 养殖家畜的冠状病毒，如猪流行性腹泻病毒（porcine epidemic diarrhea virus，PEDV），其基因序列与蝙蝠体内冠状病毒基因序列高度相似，可引起猪肠道感染并导致仔猪大量死亡，对动物健康危害极大。本研究基于对美国猪群PEDV流行毒株表观流行率的数据挖掘作为先验信息，以2019年美国生猪入境中国西南陆路口岸的实验室抗体筛查为知识更新，利用贝叶斯统计推断方法，估计美国猪群PEDV发生的真流行率分布。结果显示，PEDV在美国猪群中的真流行率分布中位值（median）为0.005 22（95% CI=0.000 424~0.022 5），95%的高置信上限（upper confident limit，UCL）的流行率分布为3%。后验分布流行率高度右偏的概率密度统计特性推断美国猪群PEDV真流行率最大可能分布主要集中在2.5%百分位数（P2.5%=0.000 2）与中位数（P50%=0.005 22）之间，但不同生猪畜群间PEDV真流行率分布值可能会存在有小概率溢出分布大于0.03（P≤2.5%）的可能。此外，在现阶段口岸筛查的试剂选择方面，建议口岸首先使用基于N蛋白的ELISA抗体作为初筛，然后以基于S1重组蛋白ELISA抗体筛查作为复筛，来提高口岸对来自美国生猪的α-冠状病毒入境我国的风险认知、管控和鉴别能力。以先验分布和口岸实验室检测结果优化为基础的贝叶斯统计推断监测技术，可以为在现有知识和认知基础上最大程度阻断来自异域病原微生物入侵提供基于科学证据的风险决策技术支持，对口岸检验检疫、抽样监测和风险决策具有突破性的意义。
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| 关 键 词： | 冠状病毒 流行性腹泻病毒 先验分布 贝叶斯推断 真流行率 监测技术 风险决策 |
| 收稿时间： | 2020-11-18 |
Bayesian Inference and Simulation on True Prevalence of Porcine Epidemic Diarrhea Virus in American Swine Population |
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| ZHANG Zhicheng,CHEN Meijuan,AI Jun.Bayesian Inference and Simulation on True Prevalence of Porcine Epidemic Diarrhea Virus in American Swine Population[J].Acta Veterinaria et Zootechnica Sinica,2021,52(7):2013-2024. |
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| Authors: | ZHANG Zhicheng CHEN Meijuan AI Jun |
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| Institution: | 1. National African Swine Fever Reference Laboratory, China Animal Health & Epidemiology Center, Qingdao 266032, China;2. Agricultural College, Ningxia University, Yingchuan 750000, China;3. Kunming Customs Technology Center, Kunming 650228, China |
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| Abstract: | The coronaviruses of livestock, such as porcine epidemic diarrhea virus-PEDV, have genetic sequences that are highly similar to those of coronaviruses in bats, which can cause intestinal infections in pigs and cause a large number of deaths of piglets, which is extremely harmful to the health of animals. This study is based on the data mining of the epidemiological prevalence of PEDV strains in the United States as a priori information, combined with antibody screening of US swine in 2019 at entry port as the knowledge update, Bayesian statistical inference were employed to estimate the true prevalence of PEDV in US swine populations. The results show that the median true prevalence (median) of PEDV in the US swine population is 0.005 22 (95% CI=0.000 424-0.022 5), and the prevalence distribution of the 95% upper confident limit (UCL) is 3%. The probability density statistical properties of the posterior distribution prevalence are highly right-skewed to infer that the true prevalence of PEDV in the U.S. pig herd is mainly concentrated between in the 2.5% percentile (P2.5%=0.0002) and the median (P50%=0.005 22), but due to the variability and difference among different pig herds in the United States, the PEDV true prevalence distribution value of a random sampling may have a small probability overflowing the distribution greater than 0.03 (P ≤ 2.5%). In addition, in terms of assay selection for port screening, it is recommended that N protein-based ELISA can be used as the primary screening method, and then use S1 recombinant protein ELISA as the re-screening method to improve the port's ability of risk perception, control and identification capabilities to mitigate the entry risk of coronavirus into the country. Bayesian statistical inference and surveillance technology based on prior distribution and optimization of port laboratory testing results can provide scientific evidence-based risk decision technology for blocking the invasion of foreign pathogenic microorganisms to the greatest extent on the basis of existing knowledge and cognition, which can be of great significance to port inspection and quarantine, sampling monitoring and risk decision-making. |
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| Keywords: | coronaviruses porcine epidemic diarrhea virus PEDV priori information Bayesian inference true prevalence surveillance technology risk decision |
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