Synthesizing the Evolutionary and Ecological Dynamics of Acute RNA Viruses: Compa

描述（由申请人提供）：直接传播的急性RNA病毒（ARV）-如甲型流感病毒和麻疹病毒-引起许多重要的人类疾病。抗逆转录病毒药物通常会引起剧烈的流行病，随着宿主的免疫系统获得对抗再感染的能力，这种流行病会因群体免疫力的增强而终止。群体免疫可以对抗逆转录病毒药物施加巨大的选择压力，使其免疫逃逸，对高突变率和大种群规模产生的广泛遗传变异起作用。这种选择的进化效应可以在流感病毒中清楚地看到，病毒表面蛋白基因的突变和选择使病毒能够重新感染宿主，破坏群体免疫力。麻疹位于进化光谱的另一端：几乎没有免疫驱动的适应性进化和近乎完美的群体免疫。因此，了解抗逆转录病毒药物的相对动态和控制取决于确定流行病学和演变过程之间的相互作用。然而，目前还没有定量的框架连接的时空疾病发病率与流行病学动态和病毒进化动力学的系统发育分析的数据。拟议的研究的目标是开发和应用这样一个框架，在一个不稳定的世界的人为变化。我们将在病毒基因序列水平和病毒亚型和血清型的组水平上进行这种合成。本工作的具体目标和方法是：1.抗逆转录病毒药物的流行病学动态和序列演变。建立和分析抗逆转录病毒药物时空传播动力学的随机重力模型，以模拟中性病毒进化和免疫逃逸。使用这个模拟框架作为一个试验台，我们将完善目前的合并方法，明确估计人口增长和下降的参数，在抗逆转录病毒药物，并适当考虑空间细分。2.抗逆转录病毒药物的群体水平应变动态和人为变化的影响。基于免疫力丧失对环境波动的人口缓冲概念，探索病毒免疫逃逸与人为/人口变化影响之间相互作用的新方法。我们将开发模型，探讨如何缓冲出生脉冲和人为变化的年龄和空间结构的宿主种群在整个观察范围内的抗逆转录病毒的生活史。3.案例研究。将联合收割机模型和系统发育方法与疾病发病率和病毒基因序列数据相结合，探讨麻疹、流感、轮状病毒、呼吸道合胞病毒和副流感病毒等5种不同且重要的人类抗逆转录病毒感染的流行病学、进化和控制中的关键问题。种群动力学和进化过程的综合是传染病生态学的关键问题。RNA病毒具有快速进化的潜力，为探索流行动力学如何驱动病原体进化提供了一个重要机会，反之亦然，以及两者如何受到人为变化的影响。该研究将为RNA病毒进化提供新的见解，澄清关键的进化和流行病学问题，并开发普遍适用的统计和建模工具。

DESCRIPTION (provided by applicant): Directly-transmitted acute RNA viruses (ARVs) - such as the influenza A and measles viruses - cause many important human diseases. ARVs typically generate violent epidemics which are terminated by the build up of herd immunity, as hosts' immune systems acquire the ability to combat reinfection. Herd immunity can impose enormous selection pressure on ARVs for immune escape, working on the extensive genetic variation generated by high mutation rates and large population sizes. The evolutionary effects of this selection can be clearly seen in influenza virus, where mutation and selection of viral surface protein genes enables the virus to re-infect hosts, subverting herd immunity. Measles lies at the other end of the evolutionary spectrum: with little immune-driven adaptive evolution and near-perfect herd immunity. Understanding the comparative dynamics and control of ARVs therefore depends on characterizing the interaction between epidemiological and evolutionary processes. However, there is currently no quantitative framework linking data on spatio-temporal disease incidence with epidemiological dynamics and phylogenetic analyses of viral evolutionary dynamics. The goal of the proposed research is to develop and apply such a framework, in a nonstationary world of anthropogenic change. We shall approach this synthesis at both viral gene sequence level and the group level of viral subtypes and serotypes. The specific objectives and methods of this work are: 1. Epidemiological dynamics and sequence evolution of ARVs. To develop and analyze computational models that superimpose both neutral viral evolution and immune escape on the current generation of stochastic gravity models for spatio-temporal transmission dynamics of ARVs. Using this simulation framework as a test-bed, we shall refine current coalescent methods to explicitly estimate the parameters of population growth and decline in ARVs and to properly account for spatial subdivision. 2. Group level strain dynamics of ARVs and the impact of anthropogenic change. To explore a new approach to the interaction between viral immune escape and the impact of anthropogenic/demographic change based on the concept of demographic buffering of environmental fluctuations by loss of immunity. We shall develop models to explore how buffering of birth pulses and anthropogenic change operates in age- and spatially-structured host populations across the observed range of ARV life histories. 3. Case studies. To combine models and phylogenetic methods with disease incidence and viral gene sequence data to explore key issues in the epidemiology, evolution and control of five contrasting and important ARV infections of humans: measles, influenza, rotavirus, respiratory syncytial virus and parainfluenza. The synthesis of population dynamic and evolutionary processes is a key problem in infectious disease ecology. With their potential for rapid evolution, RNA viruses present a major opportunity for exploring how epidemic dynamics drive pathogen evolution, and vice versa, and how both are affected by anthropogenic change. The study will provide new insights into RNA virus evolution, clarify key evolutionary and epidemiological issues, and develop generally applicable statistical and modeling tools.