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了重大的负面影响，降低了农场的生产力、盈利能力和可持续性。地方性疾病在人群中持续存在，除非得到积极控制。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，英国的地方病控制权被下放，BVD是一个例子，地方病控制权由四个下放的国家独立处理。然而，除了布鲁氏菌病，没有一个英国国家正式根除了任何地方病。为了实现地方病控制和根除的阶段性变化，需要国家和多国协调的疾病控制方法，本研究的目的是创建一种新的解决方案，以指导英国BVD国家控制计划。我们的解决方案是开发适用于英国养牛业所有部门和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数量、农场之间的移动和地理关系、不同的国家BVD控制计划进行建模，并纳入不同利益相关者的行为（农民、兽医和项目机构）和来自英国所有四个国家的整个网络的农业系统。采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。将开发模拟模型以模拟每只动物的状态，包括免疫状态（易感、暴露/免疫）和感染状态的特征。我们将把这个模型与现有的模拟模型，整个牛场连接到一个整体的环境生命周期分析模型，REMEDY。将使用现有测试数据库定义BVD的UK空间和时间模式以及模拟模型中用于代表BVD的关键流行病学和空间参数。为了建立农场之间的传播模型，我们将使用机器学习方法，根据牛群人口统计学，空间和运动数据，为英国养牛场创建一个新的分类系统。这将允许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，以创建BVD的英国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，定义当前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。将模拟利益攸关方定义的情景，并对结果的多个方面进行评价，包括流行病学、经济和环境组成部分。结果将提交给利益攸关方，并对该模型进行评价，以确定其是否有能力产生能够影响利益攸关方行为和塑造未来地方病根除方案的信息丰富和有影响力的产出。这项研究将影响英国地方病控制范围内的一系列关键利益相关者，包括动物，兽医，农民，政府，通过提供有关不同疾病控制方案的性能的重要信息以及每个下放国家方案之间的相互作用，从而允许有关控制方案和政策制定的知情讨论。该模型的遗产不仅是一个支持BVD根除的模型，而且是一个易于推广的框架，用于模拟其他牛地方病的控制。