| dc.contributor.author |
Fraile Sauce, Lorenzo José |
| dc.contributor.author |
Fernández, N. |
| dc.contributor.author |
Pena i Subirà, Ramona Natacha |
| dc.contributor.author |
Balasch, S. |
| dc.contributor.author |
Castellà, Gerard |
| dc.contributor.author |
Puig, P. |
| dc.contributor.author |
Estany Illa, Joan |
| dc.contributor.author |
Valls Marsal, Joan |
| dc.date |
2020-03-09T14:43:19Z |
| dc.date |
2021-03-07T23:21:02Z |
| dc.date |
2020-03-07 |
| dc.date |
2020-03-09T14:43:20Z |
| dc.identifier |
0167-5877 |
| dc.identifier |
https://doi.org/10.1016/j.prevetmed.2020.104948 |
| dc.identifier.uri |
http://hdl.handle.net/10459.1/68182 |
| dc.description |
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. |
| dc.description |
This study was partially funded by the FEDER project with reference COMRDI16-1-0035-03. |
| dc.format |
application/pdf |
| dc.language |
eng |
| dc.publisher |
Elsevier |
| dc.relation |
Versió postprint del document publicat a: https://doi.org/10.1016/j.prevetmed.2020.104948 |
| dc.relation |
Preventive Veterinary Medicine, 2020, vol. 177, p. 104948 |
| dc.rights |
cc-by-nc-nd, (c) Elsevier, 2020 |
| dc.rights |
http://creativecommons.org/licenses/by-nc-nd/3.0/es |
| dc.rights |
info:eu-repo/semantics/openAccess |
| dc.subject |
PRRSV circulation |
| dc.subject |
Conditional Poisson distribution |
| dc.subject |
Detection |
| dc.title |
A probabilistic Poisson-based model to detect PRRSV recirculation using sow production records |
| dc.type |
info:eu-repo/semantics/article |
| dc.type |
info:eu-repo/semantics/acceptedVersion |
