Near Real-Time Monitoring of Clinical Events Detected in Swine Herds in Northeastern Spain.

Alba-Casals A1,2, Allue E3, Tarancon V3, Baliellas J3, Novell E3, Napp S1,2, Fraile L4.

Author information

1: IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Autònoma de Barcelona, Barcelona, Spain.
2: The OIE Collaborating Centre for the Research and Control of Emerging and Re-emerging Diseases in Europe (IRTA-CReSA), Barcelona, Spain.
3: Grup de Sanejament Porcí, Lleida, Spain.
4: Departament de Ciència Animal, ETSEA, Universitat de Lleida-Agrotecnio, Lleida, Spain.

Abstract

Novel techniques of data mining and time series analyses allow the development of new methods to analyze information relating to the health status of the swine population in near real-time. A swine health monitoring system based on the reporting of clinical events detected at farm level has been in operation in Northeastern Spain since 2012. This initiative was supported by swine stakeholders and veterinary practitioners of the Catalonia, Aragon, and Navarra regions. The system aims to evidence the occurrence of endemic diseases in near real-time by gathering data from practitioners that visited swine farms in these regions. Practitioners volunteered to report data on clinical events detected during their visits using a web application. The system allowed collection, transfer and storage of data on different clinical signs, analysis, and modeling of the diverse clinical events detected, and provision of reproducible reports with updated results. The information enables the industry to quantify the occurrence of endemic diseases on swine farms, better recognize their spatiotemporal distribution, determine factors that influence their presence and take more efficient prevention and control measures at region, county, and farm level. This study assesses the functionality of this monitoring tool by evaluating the target population coverage, the spatiotemporal patterns of clinical signs and presumptive diagnoses reported by practitioners over more than 6 years, and describes the information provided by this system in near real-time. Between January 2012 and March 2018, the system achieved a coverage of 33 of the 62 existing counties in the three study regions. Twenty-five percent of the target swine population farms reported one or more clinical events to the system. During the study period 10,654 clinical events comprising 14,971 clinical signs from 1,693 farms were reported. The most frequent clinical signs detected in these farms were respiratory, followed by digestive, neurological, locomotor, reproductive, and dermatological signs. Respiratory disorders were mainly associated with microorganisms of the porcine respiratory disease complex. Digestive signs were mainly related to colibacilosis and clostridiosis, neurological signs to Glässer's disease and streptococcosis, reproductive signs to PRRS, locomotor to streptococcosis and Glässer's disease, and dermatological signs to exudative epidermitis.

KEYWORDS:

data mining; endemic diseases; endemic-epidemic multivariate time-series model; monitoring; swine health; web application

PMID:: 32133377
PMCID:: PMC7040479
DOI:: 10.3389/fvets.2020.00068

Field PRRS

Friday, March 13, 2020