Salines Morgane, Andraud Mathieu, Rose Nicolas
ANSES, Ploufragan-Plouzané Laboratory, Swine Epidemiology and Welfare Research Unit, BP 53, 22440 Ploufragan, France; Bretagne-Loire University, Rennes, France.
Prev Vet Med. 2018 Jan 1;149:125-131. doi: 10.1016/j.prevetmed.2017.11.015. Epub 2017 Nov 20.
Animal movements between farms are a major route of pathogen spread in the pig production sector. This study aimed to pair network analysis and epidemiological data in order to evaluate the impact of animal movements on pathogen prevalence in farms and assess the risk of local areas being exposed to diseases due to incoming movements. Our methodology was applied to hepatitis E virus (HEV), an emerging foodborne zoonotic agent of concern that is highly prevalent in pig farms. Firstly, the pig movement network in France (data recorded in 2013) and the results of a nation-wide seroprevalence study (data collected in 178 farms in 2009) were modelled and analysed. The link between network centrality measures of farms and HEV seroprevalence levels was explored using a generalised linear model. The in-degree and ingoing closeness of farms were found to be statistically associated with high HEV within-farm seroprevalence (p<0.05). Secondly, the risk of a French département (i.e. French local administrative areas) being exposed to HEV was calculated by combining the distribution of farm-level HEV prevalence in source départements with the number of movements coming from those same départements. By doing so, the risk of exposure for départements was mapped, highlighting differences between geographical patterns of HEV prevalence and the risk of exposure to HEV. These results suggest that not only highly prevalent areas but also those having at-risk movements from infected areas should be monitored. Pathogen management and surveillance options in the pig production sector should therefore take animal movements into consideration, paving the way for the development of targeted and risk-based disease surveillance strategies.
农场间的动物流动是生猪养殖行业病原体传播的主要途径。本研究旨在将网络分析与流行病学数据相结合，以评估动物流动对农场病原体流行率的影响，并评估当地因动物流入而接触疾病的风险。我们的方法应用于戊型肝炎病毒（HEV），这是一种新出现的食源性人畜共患病原体，在养猪场中高度流行。首先，对法国的生猪流动网络（2013年记录的数据）和一项全国性血清流行率研究的结果（2009年在178个农场收集的数据）进行建模和分析。使用广义线性模型探讨农场的网络中心性指标与戊型肝炎病毒血清流行率水平之间的联系。发现农场的入度和内向接近度与农场内戊型肝炎病毒高血清流行率在统计学上相关（p<0.05）。其次，通过将源部门农场层面戊型肝炎病毒流行率的分布与来自这些相同部门的流动数量相结合，计算法国一个省（即法国地方行政区）接触戊型肝炎病毒的风险。通过这样做，绘制了各省的接触风险图，突出了戊型肝炎病毒流行率的地理模式与接触戊型肝炎病毒风险之间的差异。这些结果表明，不仅高流行地区，而且那些有来自感染地区的风险流动的地区都应受到监测。因此，生猪养殖行业的病原体管理和监测方案应考虑动物流动，为制定有针对性的基于风险的疾病监测策略铺平道路。
