Dórea Fernanda C, Vial Flavie
Department of Disease Control and Epidemiology, National Veterinary Institute (SVA), Uppsala,
Epi-Connect, Skogås, Sweden.
Vet Med (Auckl). 2016 Nov 15;7:157-170. doi: 10.2147/VMRR.S90182. eCollection 2016.
This review presents the current initiatives and potential for development in the field of animal health surveillance (AHSyS), 5 years on from its advent to the front of the veterinary public health scene. A systematic review approach was used to document the ongoing AHSyS initiatives (active systems and those in pilot phase) and recent methodological developments. Clinical data from practitioners and laboratory data remain the main data sources for AHSyS. However, although not currently integrated into prospectively running initiatives, production data, mortality data, abattoir data, and new media sources (such as Internet searches) have been the objective of an increasing number of publications seeking to develop and validate new AHSyS indicators. Some limitations inherent to AHSyS such as reporting sustainability and the lack of classification standards continue to hinder the development of automated syndromic analysis and interpretation. In an era of ubiquitous electronic collection of animal health data, surveillance experts are increasingly interested in running multivariate systems (which concurrently monitor several data streams) as they are inferentially more accurate than univariate systems. Thus, Bayesian methodologies, which are much more apt to discover the interplay among multiple syndromic data sources, are foreseen to play a big part in the future of AHSyS. It has become clear that early detection of outbreaks may not be the principal expected benefit of AHSyS. As more systems will enter an active prospective phase, following the intensive development stage of the last 5 years, the study envisions AHSyS, in particular for livestock, to significantly contribute to future international-, national-, and local-level animal health intelligence, going beyond the detection and monitoring of disease events by contributing solid situation awareness of animal welfare and health at various stages along the food-producing chain, and an understanding of the risk management involving actors in this value chain.
本文综述了动物健康监测领域（AHSyS）自进入兽医公共卫生领域前沿5年以来的当前举措和发展潜力。采用系统综述方法记录正在进行的AHSyS举措（现行系统和处于试点阶段的系统）以及近期的方法学进展。来自从业者的临床数据和实验室数据仍是AHSyS的主要数据来源。然而，尽管目前尚未纳入前瞻性运行的举措中，但生产数据、死亡率数据、屠宰场数据和新媒体来源（如互联网搜索）已成为越来越多旨在开发和验证新的AHSyS指标的出版物的研究对象。AHSyS固有的一些局限性，如报告的可持续性和缺乏分类标准，继续阻碍自动症状分析和解释的发展。在动物健康数据普遍进行电子收集的时代，监测专家对运行多变量系统（同时监测多个数据流）越来越感兴趣，因为它们在推理上比单变量系统更准确。因此，预计更适合发现多个症状数据源之间相互作用的贝叶斯方法将在AHSyS的未来发挥重要作用。很明显，早期发现疫情可能不是AHSyS预期的主要益处。随着更多系统将进入积极的前瞻性阶段，继过去5年的密集开发阶段之后，本研究设想AHSyS，特别是针对家畜的AHSyS，将为未来国际、国家和地方层面的动物健康情报做出重大贡献，不仅限于发现和监测疾病事件，还能通过在食品生产链的各个阶段提供关于动物福利和健康的可靠态势感知，以及对该价值链中各行为体所涉及的风险管理的理解。
