Antimicrobial Stewardship for Respiratory Pathogens in Swine.

The aim of this study was to set up antimicrobial stewardship for swine respiratory pathogens following the recommendation from the European Medicine Agency. The obtained antimicrobial susceptibility pattern recommended using antimicrobial stewardship for each clinical case instead of treatment guidelines focused on pathogens. Thus, the bacteria are isolated and the MIC values, the clinical interpretation for each antimicrobial (susceptible or resistant), additional information about the distance between the MIC obtained and the clinical breakpoint, and set up for each drug, are represented in the report provided for veterinarians. A graph from green (susceptible) to red (resistant) is enclosed for each antimicrobial and microorganism in the report. The greener, the more susceptible is the strain, and the redder, the less susceptible is the strain for each particular antimicrobial. This information could help veterinarians to select the most suitable antimicrobial from first, second, or last option antimicrobials. Thus, veterinarians should choose the antimicrobial, inside each option, with the best antimicrobial susceptibility pattern that corresponds with the greener status in the report. The information provided in the report could be useful for all clinical cases, caused by a certain bacterium within the same pig production system, if an epidemiological link could be established.

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

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.