A UK platform for the control of Bovine Viral Diarrhoea:Application of a novel disease simulation model to guide programme development & policy design

英国牛病毒性腹泻控制平台：应用新型疾病模拟模型指导项目开发

• 批准号: BB/X017362/1
• 负责人: Luke O'Grady
• 金额: $ 67.05万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FX017362%2F1
• 关键词: UK; platform; control; Bovine; Viral

Endemic disease in cattle has a substantial negative impact on welfare of cattle worldwide, reduces farm productivity and profitability and sustainability. Endemic diseases persist within populations unless actively controlled. Control programmes for endemic disease in the UK have tended to focused on relatively few key conditions such as Mastitis, Bovine Viral Diarrhoea (BVD) or Johnes Disease, and implemented by individual farms, vets, or small stakeholder groups. Recently the control of endemic disease within the UK was devolved, and BVD is an example where endemic disease control is handled independently by each of the four devolved nations. However, except for brucellosis, no UK nation has officially eradicated any endemic disease. To achieve a step change in endemic disease control and eradication, national and multi-national, coordinated approaches to disease control are required and the aim of this research is to create a novel solution to guide UK national control programmes for BVD. Our solution is to develop an infectious disease simulation modelling framework applicable to all sectors across the UK cattle industry and across all nations within the UK that is capable of simultaneously modelling both cattle populations within farms, the movements and geographical relationships between farms, the different national BVD control programmes and incorporate the behaviours of different stakeholders (farmers, vets, and programme bodies) and farming systems across the entire network from all four UK nations. Use this collaborative approach will ensure development of a disease model is relevant, practical and addresses the needs of each individual country. The simulation model will be developed to model the status of each animal, including characteristics of immune status (susceptible, exposed/immune) and infection status. We will incorporate this model with an existing simulation model of a whole cattle farm linked to a holistic environmental life-cycle analysis model, REMEDY. Existing test databases will be used to define UK spatial and temporal patterns of BVD and the key epidemiological and spatial parameters to use within the simulation model to represent BVD. To establish a model of between farm spread we will use machine learning methods to create a new classification system for UK cattle farms, based on the herd demographics, spatial and movement data. This will allow a more detailed reflection of the diversity within the UK's farming population and use the newly defined classification system to simulate the trade if cattle across the networks of UK farms. The within-farm infectious disease model and the network simulation models will be combined with the analysis of the test data to create a UK wide national infectious disease simulation model of BVD. A co-design process with stakeholders will be used define current BVD control programmes and future alternative scenarios of interest and define their goals and behaviours relevant to BVD control. The scenarios defined by the stakeholders will be simulated and multiple aspects of the outcomes evaluated, including epidemiological, economic, and environmental components. The results will be presented to stakeholders and the model evaluated on the model's ability to produce informative and impactful outputs capable of influencing stakeholder behaviour and shape future endemic disease eradication programmes. This research will impact a range of key stakeholders within UK endemic disease control, including animals, vets, farmers, government, by providing vital information on the performance of different disease control scenarios ant the interactions between each of the devolved nations programmes, thus allowing for informed discussions regarding control programme and policy development. The legacy of this model will not only be a model to support BVD eradication but also, a readily generalisable framework for modelling the control of other endemic disease of cattle.

牛的地方病对全世界牛的福利产生重大负面影响，降低农场生产力、盈利能力和可持续性。除非积极控制，地方病在人群中持续存在。英国的地方病控制计划往往侧重于相对较少的关键疾病，如乳腺炎、牛病毒性腹泻 (BVD) 或约翰氏病，并由个体农场、兽医或小型利益相关者团体实施。最近，英国境内的地方病控制权被下放，BVD 就是一个例子，地方病控制权由四个下放国家各自独立处理。然而，除了布鲁氏菌病外，英国还没有哪个国家正式消灭任何地方病。为了实现地方病控制和根除的阶段性改变，需要采取国家和跨国协调的疾病控制方法，本研究的目的是创建一种新颖的解决方案来指导英国国家 BVD 控制计划。我们的解决方案是开发一个适用于英国养牛业所有部门以及英国所有国家的传染病模拟建模框架，该框架能够同时对农场内的牛群、农场之间的移动和地理关系、不同国家的牛群进行建模。 BVD 控制计划并纳入英国所有四个国家整个网络中不同利益相关者（农民、兽医和计划机构）和农业系统的行为。使用这种协作方法将确保疾病模型的开发具有相关性、实用性并满足每个国家的需求。将开发模拟模型来模拟每只动物的状态，包括免疫状态特征（易感、暴露/免疫）和感染状态。我们将把这个模型与整个养牛场的现有模拟模型结合起来，该模型与整体环境生命周期分析模型 REMEDY 相关联。现有的测试数据库将用于定义英国 BVD 的空间和时间模式以及在模拟模型中用于表示 BVD 的关键流行病学和空间参数。为了建立农场之间分布的模型，我们将使用机器学习方法，根据牛群人口统计、空间和运动数据，为英国养牛场创建一个新的分类系统。这将能够更详细地反映英国农业人口的多样性，并使用新定义的分类系统来模拟英国农场网络中的牛贸易。农场内传染病模型和网络模拟模型将与测试数据的分析相结合，创建英国范围内的BVD全国传染病模拟模型。将使用与利益相关者的共同设计流程来定义当前的 BVD 控制计划和未来感兴趣的替代方案，并定义与 BVD 控制相关的目标和行为。将模拟利益相关者定义的情景，并对结果的多个方面进行评估，包括流行病学、经济和环境因素。结果将提交给利益相关者，并根据模型产生信息丰富且有影响力的输出的能力对模型进行评估，这些输出能够影响利益相关者的行为并塑造未来的地方病根除计划。这项研究将通过提供有关不同疾病控制方案的表现以及每个权力下放国家计划之间相互作用的重要信息，对英国地方病控制范围内的一系列关键利益相关者产生影响，包括动物、兽医、农民、政府，从而允许有关控制计划和政策制定的知情讨论。该模型的遗产不仅是支持根除 BVD 的模型，而且是一个易于推广的框架，用于对牛的其他地方病的控制进行建模。