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一种基于泊松概率的模型,用于利用母猪生产记录检测 PRRSV 的再循环。

A probabilistic Poisson-based model to detect PRRSV recirculation using sow production records.

机构信息

Department of Animal Science, University of Lleida - Agrotecnio Center, Lleida, Spain.

Biostatistics and Epidemiology Unit, Biomedical Research Institute of Lleida (IRB Lleida), Lleida, Spain.

出版信息

Prev Vet Med. 2020 Apr;177:104948. doi: 10.1016/j.prevetmed.2020.104948. Epub 2020 Mar 7.

Abstract

Porcine reproductive and respiratory syndrome (PRRS) is a viral disease associated with a decrease in the number of born alive piglets (NBA) and an increase in the number of lost piglets (NLP) per farrowing. Under practical conditions, it is critical to assess whether a farm is suffering PRRSV recirculation in the sow herd as soon as possible. The aim of this research work was to develop a new method to detect potential PRRSV recirculation in sow production farms. Sow reproductive performance records from one farm (farm T) were used to set up the method and records from ten additional farms (farms V1 to V10) were used for validation. A conditional Poisson model of NLP on NBA was proposed to fit the data. A three-step procedure was implemented to detect potential PRRSV recirculation: (i) computation of the maximum-likelihood estimates of the expected values of NBA and NLP in a PRRSV non-recirculating scenario; (ii) calculation, for each farrowing, of the p-value associated with the probability of jointly observing deviations towards decreased NBA and increased NLP. The detection of a potential PRRSV recirculation was based on (iii) the combined p-value resulting from weighing the p-values of the last N farrowings by the chi-square-inverse method. In order to gain specificity, a displacement on the expected non-recirculating NBA and NLP values was used for tuning purposes. With this approach, two PRRSV circulating periods were detected in farm T, which were confirmed with standard laboratorial diagnostic techniques. The method was subsequently validated in farms V1 to V10, where ten PRRSV-recirculating time episodes had been diagnosed. The method proposed here was able to detect the ten PRRSV recirculations using a relatively small set of contiguous farrowings, with only two mismatched weeks, one as a false negative, in farm V1, and one as a false positive, in farm V4. It is concluded that a conditional Poisson-based model of NLP on NBA can be a useful tool for routinely detecting PRRSV recirculation in sow herds.

摘要

猪繁殖与呼吸综合征(PRRS)是一种与每窝产活仔数(NBA)减少和每窝损失仔猪数(NLP)增加相关的病毒病。在实际情况下,尽快评估猪场母猪群中是否存在 PRRSV 再循环是至关重要的。本研究工作的目的是开发一种新的方法来检测母猪生产农场中潜在的 PRRSV 再循环。使用一个农场(农场 T)的母猪繁殖性能记录来建立该方法,并使用另外十个农场(农场 V1 到 V10)的记录进行验证。提出了一个 NBA 上 NLP 的条件泊松模型来拟合数据。实施了一个三步程序来检测潜在的 PRRSV 再循环:(i)在 PRRSV 非循环情况下计算 NBA 和 NLP 的期望值的最大似然估计;(ii)对于每个分娩,计算联合观察到 NBA 减少和 NLP 增加的概率的相关 p 值。潜在的 PRRSV 再循环的检测基于(iii)通过使用卡方倒数法对最后 N 个分娩的 p 值进行加权的综合 p 值。为了提高特异性,使用了偏离预期的非循环 NBA 和 NLP 值进行调优。使用这种方法,在农场 T 中检测到了两个 PRRSV 循环期,这些循环期得到了标准实验室诊断技术的证实。该方法随后在农场 V1 到 V10 中进行了验证,在这些农场中已经诊断出十个 PRRSV 再循环时间事件。所提出的方法能够使用相对较小的连续分娩集来检测十个 PRRSV 再循环,只有两个不匹配的星期,一个是农场 V1 的假阴性,一个是农场 V4 的假阳性。因此,基于 NBA 上 NLP 的条件泊松模型可以成为一种有用的工具,用于常规检测母猪群中的 PRRSV 再循环。

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