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Use of contact structures for the control of infectious diseases in the British aquaculture industry

在英国水产养殖业中使用接触结构来控制传染病

基本信息

批准号：
BB/M026434/1
负责人：
Kieran Sharkey
金额：
$ 27.52万
依托单位：
University of Liverpool
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2015
资助国家：
英国
起止时间：
2015 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FM026434%2F1
关键词：
Use contact structures control infectious

项目摘要

Infectious fish diseases present an ongoing threat to the British Aquaculture Industry. Britain has so far been fortunate in avoiding large-scale outbreaks of major infectious diseases such as Viral Haemorrhagic Septicaemia, Gyrodactylus salaris and Infectious Haematopoietic Necrosis. However, these diseases are prevalent in parts of Europe and could potentially have serious economic implications for British Aquaculture. This research project aims to develop the capacity to understand, prevent and control outbreaks of these and other infectious diseases. Working with project partners at Marine Scotland and the Centre for Environment, Fisheries & Aquaculture Science (Cefas), we will assimilate existing detailed information from England, Scotland and Wales on the structure and operation of the British Aquaculture industry into the first single network of disease transmission routes between fish farms and fisheries throughout Britain. This structure will be analysed using modern methods from network theory to identify properties that will assist and inform the design of optimal strategies for the control and prevention of fish disease epidemics. In particular, by running computer simulations of large and small epidemics upon this realistic network, we will identify the full range of behaviours and test the efficacy of possible interventions. Acting in a similar way to weather forecasting, running millions of simulations will enable us to test the full breadth of possible outbreak scenarios, and establish their general likelihoods, as well as profiling high-risk spreading dynamics originating at any specific site or site cluster we choose. In addition, this "numerical laboratory" lets us explore and fine-tune a broad range of existing and novel containment, mitigation, and eradication policies These measures range from site-specific controls, through local contact tracing, to nationwide measures (e.g., a stakeholder-targeted awareness campaign of specific symptoms to look out for), while simultaneously imposing realistic capacity constraints. Analysis of interventions will also have an associated economic costing, as it would clearly be counter-productive to engage in an intervention strategy that was as costly as the infectious disease itself. The overall aim here is not just exploratory and analytical, but, moreover, to create a practical, flexible expert system that can be fed the latest data on the (slowly changing) network architecture, pathogen properties, and any emerging outbreak, and be able to produce accurate real-time risk assessments of spreading dynamics, as well as being able to suggest the most effective counter-strategies given specific locations and circumstances.Finally, an unusual property of fish pathogens is that their properties and effects are often temperature-dependent in terms of their infectivity, the extent infections cause recognisable symptoms, and fish mortality. An important goal of this work is therefore to include farm-specific temperature data into the representation of epidemic spread on the network. This is part of a wider strategy to model the system across multiple scales whereby other farm-specific data such as size, type and production can feed into the model. Such farm-level sub-models will be readily changeable to maximise adaptability of the simulator for future research. In this respect, we specifically aim to address the effects of climate change (over years to decades) in terms of higher water temperatures impacting fish disease epidemics. As far as we are aware, no-one has ever investigated the scale and severity of these future impacts on the British Aquaculture industry, and we need to be (better) prepared. This project thus aspires to create a durable foundation of field expertise, scientific insights, and data on the British Aquaculture Industry, to safeguard its future success in the face of ongoing epidemic threats.

传染性鱼类疾病对英国水产养殖业构成持续威胁。迄今为止，英国幸运地避免了病毒性出血性败血症、柳三代虫和传染性造血器官坏死等重大传染病的大规模爆发。然而，这些疾病在欧洲部分地区流行，可能会对英国水产养殖业产生严重的经济影响。该研究项目旨在发展了解、预防和控制这些疾病和其他传染病爆发的能力。与苏格兰海洋和环境，渔业和水产科学中心（Cefas）的项目合作伙伴合作，我们将吸收英格兰，苏格兰和威尔士现有的关于英国水产业结构和运作的详细信息，并将其纳入整个英国养鱼场和渔业之间的疾病传播途径的第一个单一网络。将使用网络理论的现代方法来分析这种结构，以确定有助于设计和通知控制和预防鱼病流行病的最佳策略的属性。特别是，通过在这一现实网络上运行大小流行病的计算机模拟，我们将确定各种行为，并测试可能的干预措施的有效性。以类似于天气预报的方式，运行数百万次模拟将使我们能够测试可能爆发情景的全部范围，并确定其一般可能性，以及分析源自我们选择的任何特定站点或站点群的高风险传播动态。此外，这个“数字实验室”让我们探索和微调广泛的现有和新的遏制，缓解和根除政策。这些措施包括从特定地点的控制，通过当地接触者追踪，到全国范围的措施（例如，针对需要注意的具体症状的知识产权持有人的宣传运动），同时施加现实的能力限制。对干预措施的分析也会产生相关的经济成本，因为参与与传染病本身一样昂贵的干预战略显然会适得其反。这里的总体目标不仅仅是探索性和分析性的，而且，创建一个实用的，灵活的专家系统，可以提供最新的数据，（缓慢变化的）网络架构、病原体特性和任何新出现的疫情，并能够对传播动态进行准确的实时风险评估，以及能够在特定的地点和情况下提出最有效的应对策略。最后，鱼类病原体的一个不寻常的特性是，它们的特性和影响在它们的感染性、感染引起可识别症状的程度和鱼类死亡率方面通常依赖于温度。因此，这项工作的一个重要目标是将农场特定的温度数据纳入网络上流行病传播的表示中。这是在多个尺度上对系统进行建模的更广泛战略的一部分，从而可以将其他农场特定的数据（如大小，类型和产量）输入模型。这样的农场级子模型将很容易改变，以最大限度地提高模拟器的适应性，为未来的研究。在这方面，我们的具体目标是解决气候变化（多年至数十年）对水温升高影响鱼病流行的影响。据我们所知，还没有人调查过这些未来对英国水产养殖业影响的规模和严重程度，我们需要做好（更好）准备。因此，该项目旨在为英国水产养殖业的专业知识、科学见解和数据奠定持久的基础，以确保其在面临持续流行病威胁的情况下取得未来的成功。