Risk factors for escalating saprolegniosis outbreaks in salmon farms (RIFE-SOS)

鱼类疾病是水产养殖业和全球粮食安全的巨大威胁。水产养殖中一些最重要的致病生物是卵菌或水霉菌的一部分，特别是寄生水霉、diclina水霉和australis水霉正在造成严重的鱼类损失。总的来说，这些真菌样生物体在大多数鲑鱼孵化场和淡水地点造成至少10%的年死亡率。不幸的是，在过去的几年里，苏格兰养殖场的水霉病爆发的发生率显着增加。事实上，一些地点由于水霉病造成了非常高的损失。而其他农场基本上没有疾病。为什么一些农场受到严重影响，而另一些农场似乎避免了疾病爆发，具有明显相同的福利标准和畜牧业管理模式，目前的原因完全不清楚，这是目前申请的主要理由。（与鱼类、病原体和环境有关）在抑制鱼类对水霉属的免疫力方面发挥协同作用，导致水霉病的爆发因此，我们提出了一个协调一致的行业范围内，行业主导和行业支持的研究计划，以发现，映射，建模和了解允许水霉病爆发的主要驱动因素和风险因素。将创建一个“大数据”资源，用统计方法仔细检查，以确定水霉病爆发的主要风险因素和条件。毫无疑问，确定主要的风险因素或风险因素的组合将大大有助于鲑鱼水产养殖业预先预防未来的任何爆发，并将导致对水霉病管理采取综合办法，这将导致提高福利标准，改善鱼类健康，减少损失并降低生产和处理成本。

Fish diseases are a huge threat for the aquaculture industry and for global food security. Some of the most important disease-causing organisms in aquaculture are part of the oomycetes or watermoulds, in particular Saprolegnia parasitica, Saprolegnia diclina and Saprolegnia australis are causing serious fish losses. Collectively, these fungal-like organisms are responsible for at least 10% annual mortalities in most salmon hatcheries and freshwater sites. Consequently, Saprolegnia ranks among the most important pathogens of Atlantic salmon.Unfortunately, over the last few years the incidences of saprolegniosis outbreaks in Scottish farms have significantly increased. Indeed, some sites have had very high losses due to saprolegniosis. Whereas other farms have remained largely disease free. The reasons as to why some farms are badly affected and others seem to avoid disease outbreaks, with apparent identical welfare standards and husbandry management practises, are at present completely unclear and form the main rational for the current application.Our hypothesis is that several risk factors (pertaining to fish, pathogens and the environment) are playing a synergistic role in suppressing immunity in fish towards Saprolegnia, which lead to outbreaks of saprolegniosis. Therefore, we propose a concerted industry-wide, industry-led and industry-supported research programme to discover, map, model and understand the main drivers, risk factors, that allow saprolegniosis outbreaks. A "big data" resource will be created that will be scrutinised with statistical methods to identify the main risk factors and conditions for outbreaks of saprolegniosis. Undoubtedly, identifying the main, or a combination of, risk factors will greatly aid the salmon aquaculture industry to pre-empt any future outbreaks and would lead to an integrated approach to saprolegniosis management, which would result in increased welfare standards, improved fish health, fewer losses and a reduction in production and treatment costs.