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.

中文翻译：

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一种基于泊松概率的模型，可使用母猪生产记录检测PRRSV再循环。

猪繁殖与呼吸综合症（PRRS）是一种病毒性疾病，与每个分娩的活仔猪（NBA）数量减少和仔猪损失（NLP）数量增加有关。在实际条件下，至关重要的是尽快评估农场是否正在母猪群中遭受PRRSV再循环。这项研究工作的目的是开发一种新方法，以检测母猪生产场中潜在的PRRSV再循环。使用来自一个农场（农场T）的母猪生殖性能记录来建立该方法，并使用来自另外十个农场（农场V1至V10）的记录进行验证。提出了基于NBA的NLP条件Poisson模型以拟合数据。实施了三步过程以检测潜在的PRRSV再循环：（i）在PRRSV非循环情况下计算NBA和NLP期望值的最大似然估计；（ii）为每个分娩计算p值，该p值与共同观察朝向NBA减少和NLP增加的偏差的概率有关。可能的PRRSV再循环的检测基于（iii）通过卡方平方方法对最后N个产仔的p值进行加权得到的组合p值。为了获得特异性，将预期的非循环NBA和NLP值的位移用于调整目的。通过这种方法，在农场T中检测到两个PRRSV循环期，并通过标准实验室诊断技术进行了确认。此方法随后在农场V1到V10中进行了验证，已诊断出十例PRRSV循环时间发作。这里提出的方法能够使用相对较小的一组连续分娩来检测十次PRRSV再循环，只有两个不匹配的星期，在农场V1中一个为假阴性，而在农场V4中一个为假阳性。结论是，基于条件泊松的NBA NLP模型可以作为常规检测母猪PRRSV再循环的有用工具。