A mathematical immuno-epidemiological framework for co-infection

共同感染的数学免疫流行病学框架

• 批准号: 342116-2013
• 负责人: Heffernan, Jane
• 金额: $ 1.38万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=635690
• 关键词: mathematical; immuno; epidemiological; framework; co

With the advent of the germ theory of disease, understanding the mechanisms of pathogen propagation and survival has formed a major branch of the natural sciences. Mathematical immunology (in a host) and epidemiology (in a population) have contributed to the study of infectious diseases. Recently, the field of immuno-epidemiology, whereby immunological characteristics are incorporated into epidemiological models, has been developed so that a better understanding of effects of pathogen and immune system interactions on disease transmission and persistence in a population can be gained. This applied mathematics proposal focuses on the development of a mathematical immuno-epidemiological framework for co-infection, when two pathogens simultaneously infect a host, and a population. Our overriding objective is to understand how synergism between co-infecting pathogens influence disease progression and propagation. As a model system, we will focus on the globally relevant Human Immunodeficiency Virus- mycobacterium Tuberculosis (HIV-TB) co-infection. TB and HIV are both diseases which plague the globe. These diseases also contribute to the propagation of the other in-host and in a population. By defining the parameters critical to HIV-TB co-infection, this work will provide an enhanced understanding of the effects of synergy in pathogenesis and, ultimately, a basis for the improved care of HIV/TB patients. The primary research outcome of the proposed work will be a mathematically tractable and biologically relevant immuno-epidemiological modelling framework of co-infection. New mathematical and computational tools will result in the areas of global stability analysis, bifurcation theory, moment closure and stochastic modelling. Theory and techniques for qualitative analysis of the large systems are developed, as well as robust and efficient numerical and stochastic tools. These approaches can readily be translated to other co-infection systems (i.e. Leishmaniasis-HIV, HIV-HBV, etc), extended to study drug therapy and vaccination limitations/effectiveness, and to study infection spread in a network of populations linked by travel.

随着疾病的细菌理论的出现，了解病原体繁殖和存活的机制已经形成了自然科学的一个主要分支。数学免疫学（在宿主中）和流行病学（在人群中）对传染病的研究做出了贡献。最近，免疫流行病学领域，其中免疫学特征被纳入流行病学模型，已被开发，以便更好地了解病原体和免疫系统的相互作用对疾病的传播和持久性在人群中的影响，可以获得。这一应用数学的建议侧重于发展一个数学免疫流行病学框架的共同感染，当两种病原体同时感染一个主机，和人口。我们的首要目标是了解共感染病原体之间的协同作用如何影响疾病的进展和传播。作为一个模型系统，我们将重点关注全球相关的人类免疫缺陷病毒-结核分枝杆菌（HIV-TB）合并感染。结核病和艾滋病毒都是困扰地球仪的疾病。这些疾病也有助于其他宿主和种群的传播。通过确定艾滋病毒-结核病合并感染的关键参数，这项工作将提供一个更好的理解的协同作用的发病机制，并最终为改善艾滋病毒/结核病患者的护理的基础。拟议工作的主要研究成果将是一个数学上易于处理和生物学相关的免疫流行病学模型框架的共同感染。新的数学和计算工具将导致在全球稳定性分析，分叉理论，时刻关闭和随机建模领域。理论和技术的定性分析的大系统的开发，以及强大而有效的数值和随机工具。这些方法可以很容易地转化为其他共感染系统（即利什曼病-HIV，HIV-HBV等），扩展到研究药物治疗和疫苗接种的局限性/有效性，并研究通过旅行联系的人群网络中的感染传播。