Alba-Casals Ana, Allue Eduard, Tarancon Vicens, Baliellas Jordi, Novell Elena, Napp Sebastián, Fraile Lorenzo
IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Autònoma de Barcelona, Barcelona, Spain.
The OIE Collaborating Centre for the Research and Control of Emerging and Re-emerging Diseases in Europe (IRTA-CReSA), Barcelona, Spain.
Front Vet Sci. 2020 Feb 18;7:68. doi: 10.3389/fvets.2020.00068. eCollection 2020.
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.
数据挖掘和时间序列分析的新技术使得开发新方法以近乎实时地分析与猪群健康状况相关的信息成为可能。自2012年以来，西班牙东北部一直在运行一个基于农场层面检测到的临床事件报告的猪健康监测系统。该倡议得到了加泰罗尼亚、阿拉贡和纳瓦拉地区的养猪利益相关者和兽医从业者的支持。该系统旨在通过收集来自访问这些地区养猪场的从业者的数据，近乎实时地证明地方病的发生情况。从业者自愿使用网络应用程序报告他们在访问期间检测到的临床事件数据。该系统允许收集、传输和存储关于不同临床症状的数据，对检测到的各种临床事件进行分析和建模，并提供具有更新结果的可重复报告。这些信息使该行业能够量化养猪场地方病的发生情况，更好地识别其时空分布，确定影响其存在的因素，并在地区、县和农场层面采取更有效的预防和控制措施。本研究通过评估目标人群覆盖范围、从业者在6年多时间里报告的临床症状和推定诊断的时空模式，评估了该监测工具的功能，并描述了该系统近乎实时提供的信息。在2012年1月至2018年3月期间，该系统覆盖了三个研究地区62个现有县中的33个。目标猪群养殖场的25%向该系统报告了一个或多个临床事件。在研究期间，共报告了10654起临床事件，包括来自1693个养殖场的14971个临床症状。在这些养殖场中检测到的最常见临床症状是呼吸道症状，其次是消化、神经、运动、生殖和皮肤症状。呼吸道疾病主要与猪呼吸道疾病综合征的微生物有关。消化症状主要与大肠杆菌病和梭菌病有关，神经症状与格拉泽氏病和链球菌病有关，生殖症状与猪繁殖与呼吸综合征有关，运动症状与链球菌病和格拉泽氏病有关，皮肤症状与渗出性皮炎有关。
