Modelling the spread of disease in honey bees, and predicting the efficacy of control methods.

开发常见蜜蜂疾病和病原体的二维时空确定性模型，以了解如何更好地控制和消除它们。一个基本的生态问题是感染的空间规模如何影响根除。我们将使用来自英国和其他岛屿的数据来解决何时可以消除入侵者的问题。这将通过使用与MCMC方法的数据相匹配的模型来完成。例如，Datta et al 2013（Modeling the spread of American foulbrood in honeybees）使用2D空间模型来模拟泽西岛疾病的传播，该模型还发现了同一养蜂人拥有的养蜂场之间的联系。然后，这些信息可以用于确定控制方法将如何影响系统。这是我想做的研究的一个例子。蜜蜂疾病在真实的世界中至关重要，因为蜜蜂是全球农业的重要组成部分。英国国家蜜蜂研究所支持英格兰各地的蜜蜂疾病和护理研究。在该项目期间，还将寻求其他国家和地区的合作。研究的背景-蜜蜂疾病在真实的世界中至关重要，因为蜜蜂在授粉服务方面是全球农业的重要组成部分。例如，瓦螨尚未入侵澳大利亚，因此了解瓦螨如何传播（无论传播主要是蜂巢到蜂巢，还是同一饲养者拥有的蜂巢之间）可以允许更有效地实施控制方法。研究的目的和目标- 1）开发蜜蜂疾病传播的时空模型，并预测控制方法的有效性。2）将模型与一些入侵案例研究的数据相匹配。3）了解入侵和控制，以及这是如何受到景观隔离的影响。研究方法的新奇-关于疾病在蜜蜂中传播的详细模型很少。关于入侵害虫的空间尺度和控制的一般性问题研究很少，也缺乏好的方法。除口蹄疫外，普遍缺乏商业牲畜疾病的模型。此外，养蜂业一般没有执照，也不受管制，因此缺乏高质量的数据。这也是由于政府机构缺乏兴趣。潜在的影响，应用和好处-我的研究可用于预测疾病在管理蜜蜂种群中的传播。它可能会建议更好的有针对性的控制方法，或者可能会强调什么时候控制是不可能的。研究如何与职权范围相关-这项研究福尔斯属于EPSRC的主题“与环境变化共存”，“全球不稳定”和“数学科学”-使用数学模型来考虑入侵管理种群。它与EPRSC的研究领域重叠：复杂性科学、数学生物学、非线性系统、统计学和应用概率。研究领域;全球不确定性、LWEC [与环境变化共存]、数学科学外部合作伙伴-国家水和大气研究所

Develop 2D spatio-temporal deterministic models of common honey-bee diseases and pathogens to understand how they can be better controlled and eliminated. A fundamental ecological question is how the spatial scale of infection influences eradication. We will look to use data from the UK and other islands to address the question of when invaders can be eliminated.This will be done through the use of models matched to data through MCMC methods.For example, Datta et al 2013 (Modelling the spread of American foulbrood in honeybees) used a 2D spatial model to model spread of disease in Jersey which also found links between apiaries owned by the same beekeeper. This information can then be used to identify how control methods will impact the system. This is an example of the kind of research I would like to do.Bee disease is critical in the real world because bees are an important part of global agriculture. The National Bee Unit supports research into bee disease and care across England.Collaborations in other countries and regions will also be sought during the project.The context of the research - Bee disease is critical in the real world because honey bees are an important part of global agriculture in terms of pollination services. For example, Varroa Destructor has not yet invaded Australia, and therefore understanding how varroa spreads (whether transmission is mostly hive to hive, or between hives owned by the same keeper) may allow for control methods to be implemented more efficiently.The aims and objectives of the research - 1) Development of spatio-temporal models for the spread of disease in bees, and prediction of control methods efficacy.2) Matching models against data for a number of case studies of invasion.3) Develop an understanding of invasion and control, and how this is affected by segregation of the landscape.The novelty of the research methodology - There are very few detailed models of disease spread in honey bees. The generic question about spatial scales and control of invasive pest is poorly studied, and there's also a lack of good methodology. Apart from foot and mouth disease, there is a general lack of modelling of commercial live stock diseases. Furthermore, bee keeping is generally unlicensed and unregulated, so there is a lack of high quality data. This is also due to the lack of interest from government bodies.The potential impact, applications, and benefits - My research could be used to predict the spread of disease in managed honey bee populations. It may suggest better methods of targeted control, or may highlight when control is impossible.How the research relates to the remit - This research falls into EPSRC Themes of "Living with Environmental Change", "Global Uncertainties" and "Mathematical Sciences" - using mathematical models to consider invasion in managed populations.It overlaps with EPRSC Research Areas: Complexity science, Mathematical Biology, Nonlinear systems, Statistics and applied probability.Research area; Global uncertainties, LWEC [Living With Environmental Change], Mathematical SciencesExternal Partner - National Institute of Water and Atmospheric Research