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Can metabolic control analysis be used to control epidemics?

代谢控制分析可以用来控制流行病吗？

基本信息

批准号：
EP/J00474X/1
负责人：
Kieran Sharkey
金额：
$ 12.34万
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：
2012
资助国家：
英国
起止时间：
2012 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FJ00474X%2F1
关键词：
metabolic control analysis used epidemics

项目摘要

Our recent mathematical modelling has shown that H5N1 avian influenza in the British poultry industry can be controlled more (cost) effectively by targeting duck and goose farms than by more general intervention strategies applied equally to all farms. Indeed, these targeted interventions were shown to mitigate the chance of large outbreaks altogether.The present research is a feasibility study to develop a general framework for designing targeted interventions to prevent and control epidemics. It is based on recent mathematical developments in the representation of epidemics on networks which enable ideas from systems biology to be applied in this new area. These methods are particularly relevant for epidemics in livestock industries where the structure is often well described by individual farms connected by a contact network of potential infection routes. Current measures for controlling epidemics in these industries often rely on general policies of increased biosecurity, vaccination, culling or movement bans. While these approaches are demonstrably effective, more targeted applications of these methods are likely to be less intrusive to the operation of industry as well as being cheaper to implement.Epidemics are examples of complex systems where system-wide factors such as their size, likelihood, and control are emergent behaviours resulting result from the interaction of many individual components. In addition to other many other areas, problems concerning the control of complex systems also occur in systems biology where we also wish to alter network functionality by targeted interventions to help us gain understanding and to generate medical and industrial applications. For example, these could be to maximise the generation of a particular chemical for industrial purposes (e.g. ethanol in yeast) or for medical applications (e.g. determining key interventions which will destroy a tumour cell while leaving healthy cells unharmed). That is, we want to achieve the maximum positive effect with the minimum targeted intervention.In systems biology, a form of control theory known as Metabolic Control Analysis (MCA) is used to determine the impact of specific interventions on living (typically single-cell) organisms. This project will develop related ideas to design targeted interventions to prevent or control epidemics. The application of an MCA-like theory in this context requires some novel mathematical developments but, where possible, its development will be inspired by comparison with MCA. Targeted intervention to control infection in livestock is clearly of significant importance, not only for the welfare of the animals but also for the economic impact on industry and the wider economy. This analysis could also identify key sites or risk factors for epidemics enabling preventative measures to be put into place such that an epidemic rarely occurs.A more subtle benefit from this research is to establish a stronger link between the methods used in systems biology and the methods used in epidemiology. Presently these subjects evolve quite independently but have notable methodological similarities. It is expected that this research will contribute to closer links, with ideas developed and implemented in one area inspiring ideas in the other.

我们最近的数学模型显示，英国家禽业的H5N1禽流感可以通过针对鸭场和鹅场的更有效的(成本)控制，而不是通过对所有农场平等地应用更普遍的干预策略。事实上，这些有针对性的干预措施被证明总体上减少了大规模暴发的机会。本研究是一项可行性研究，旨在为制定预防和控制流行病的有针对性干预措施的一般框架进行可行性研究。它是基于在网络上表示流行病的最新数学发展，这使得系统生物学的想法能够应用于这一新领域。这些方法对于畜牧业的流行病特别相关，在畜牧业中，通过潜在感染途径的联系网络连接的单个农场往往很好地描述了这种结构。目前在这些行业控制流行病的措施往往依赖于加强生物安全、接种疫苗、扑杀或禁止行动的一般政策。虽然这些方法被证明是有效的，但这些方法更有针对性的应用可能对工业运行的干扰较小，而且实施成本更低。流行病是复杂系统的例子，其中系统范围的因素，如其大小、可能性和控制，是许多单独组件相互作用产生的紧急行为。除了其他许多领域外，有关复杂系统控制的问题也出现在系统生物学中，我们也希望通过有针对性的干预来改变网络功能，以帮助我们获得理解并产生医疗和工业应用。例如，这可能是为了最大限度地产生一种特定的化学物质，用于工业目的(例如酵母中的乙醇)或医疗应用(例如确定在不损害健康细胞的情况下摧毁肿瘤细胞的关键干预措施)。在系统生物学中，一种被称为代谢控制分析(MCA)的控制理论被用来确定特定干预措施对活的(通常是单细胞)生物的影响。该项目将提出相关想法，以设计有针对性的干预措施，以预防或控制流行病。在这种情况下应用类似MCA的理论需要一些新的数学发展，但在可能的情况下，它的发展将受到与MCA的比较的启发。控制家畜感染的针对性干预显然非常重要，这不仅对动物的福利，而且对工业和更广泛的经济产生经济影响。这种分析还可以确定流行的关键地点或风险因素，从而能够实施预防措施，使流行病很少发生。这项研究的一个更微妙的好处是在系统生物学中使用的方法和流行病学中使用的方法之间建立了更紧密的联系。目前，这些主题的发展相当独立，但在方法论上有显著的相似之处。预计这项研究将有助于建立更紧密的联系，在一个领域制定和实施的想法在另一个领域激发想法。