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Spatial and Functional Organization of Pig Trade in Different European Production Systems: Implications for Disease Prevention and Control

机译:欧洲不同生产系统中生猪贸易的空间和功能组织:对疾病预防和控制的意义

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摘要

Understanding the complexity of live pig trade organization is a key factor to predict and control major infectious diseases, such as classical swine fever (CSF) or African swine fever (ASF). Whereas the organization of pig trade has been described in several European countries with indoor commercial production systems, little information is available on this organization in other systems, such as outdoor or small-scale systems. The objective of this study was to describe and compare the spatial and functional organization of live pig trade in different European countries and different production systems. Data on premise characteristics and pig movements between premises were collected during 2011 from Bulgaria, France, Italy, and Spain, which swine industry is representative of most of the production systems in Europe (i.e., commercial vs. small-scale and outdoor vs. indoor). Trade communities were identified in each country using the Walktrap algorithm. Several descriptive and network metrics were generated at country and community levels. Pig trade organization showed heterogeneous spatial and functional organization. Trade communities mostly composed of indoor commercial premises were identified in western France, northern Italy, northern Spain, and north-western Bulgaria. They covered large distances, overlapped in space, demonstrated both scale-free and small-world properties, with a role of trade operators and multipliers as key premises. Trade communities involving outdoor commercial premises were identified in western Spain, south-western and central France. They were more spatially clustered, demonstrated scale-free properties, with multipliers as key premises. Small-scale communities involved the majority of premises in Bulgaria and in central and Southern Italy. They were spatially clustered and had scale-free properties, with key premises usually being commercial production premises. These results indicate that a disease might spread very differently according to the production system and that key premises could be targeted to more cost-effectively control diseases. This study provides useful epidemiological information and parameters that could be used to design risk-based surveillance strategies or to more accurately model the risk of introduction or spread of devastating swine diseases, such as ASF, CSF, or foot-and-mouth disease.
机译:了解生猪贸易组织的复杂性是预测和控制主要传染病(例如经典猪瘟(CSF)或非洲猪瘟(ASF))的关键因素。尽管在几个欧洲国家中使用室内商业生产系统描述了生猪贸易的组织,但是在其他系统(例如室外或小型系统)中,关于该组织的信息很少。这项研究的目的是描述和比较不同欧洲国家和不同生产系统中生猪贸易的空间和功能组织。有关养猪场特征和养猪场之间移动的数据是在2011年期间从保加利亚,法国,意大利和西班牙收集的,其中养猪业是欧洲大多数生产系统的代表(即,商业,小型,室外与室内) )。使用Walktrap算法在每个国家/地区中确定了贸易社区。在国家和社区级别生成了一些描述性和网络指标。养猪贸易组织显示出异质的空间和功能组织。在法国西部,意大利北部,西班牙北部和西北保加利亚确定了主要由室内商业场所组成的贸易社区。它们覆盖了很长一段距离,在空间上重叠,展示了无标度和小世界特性,并且以贸易运营商和乘数为主要前提。在西班牙西部,西南部和法国中部发现了涉及户外商业场所的贸易社区。它们在空间上更加聚类,表现出无标度的特性,并且乘数是关键前提。小型社区涉及保加利亚以及意大利中部和南部的大部分房屋。它们在空间上聚集并且具有无标度特性,主要前提通常是商业生产场所。这些结果表明,疾病可能会根据生产系统而有很大不同,并且关键前提可能针对更具成本效益的疾病控制。这项研究提供了有用的流行病学信息和参数,可用于设计基于风险的监视策略或更准确地为破坏性猪病(例如ASF,CSF或口蹄疫)引入或传播的风险建模。

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