Spillover of Ebola and other filoviruses at ecological boundaries

全球一半以上的传染病暴发是人畜共患病，涉及病原体从动物宿主向人类的溢出。埃博拉病毒和其他丝状病毒属于最致命的人畜共患病。最近的大规模暴发，在人类和野生动物中都有数千人死亡，这突显了更好地了解促进丝状病毒溢出的因素的迫切需要。尽管溢出通常被定义为跨越物种边界的病原体，但明确考虑发生溢出的生态边界的实证研究或建模框架相对较少。跨越生态边界涉及在许多组织层次上发生的过程：个体水平上的生理过程、种群水平上个体间的种间相互作用、群落水平上不同物种种群之间的相互作用，以及景观内生态群落之间的相互作用。加速溢出的过程往往涉及人类活动，如栖息地侵占和土地转换，而这些活动本身最终是由社会经济因素驱动的。在非洲埃博拉和其他丝状病毒的背景下，我们将开发所需的数据集、理论模型和统计工具，以建立生态边界溢出的一般描述性和预测性框架。我们的项目将遵循迭代设计，其中来自机械模型的结果被用于精炼我们经验性测试的模式，而大规模数据的统计模型允许我们更现实地将机械模型参数化。我们的工作将测试到目前为止只应用于有限数量的研究系统的特定理论的普遍性。例如，我们将是第一批测试施马尔豪森定律对依赖直接传播的病原体的影响的尝试之一。施马尔豪森定律是一种进化论，可以解释在物种范围的边缘或在不寻常的天气条件下发生大爆发的趋势，迄今主要是在疟疾的背景下进行研究。这项工作将展示新方法如何提供对至关重要的疾病传播系统中的模式的统一洞察，并将增强我们预测丝状病毒和许多其他人畜共患病病原体溢出的能力。请注意，该项目将不涉及任何人类受试者、生物危害或选定的制剂。

More than half of all infectious disease outbreaks across the globe are zoonotic, involving pathogen spillover from animal reservoirs to humans. Ebola and other filoviruses rank among the most deadly zoonoses. Recent large outbreaks with mortality in the thousands both in humans and wildlife underscore the pressing need to better understand the factors promoting filovirus spillover. Although spillover is commonly defined as a pathogen crossing species boundaries, there are relatively few empirical studies or modeling frameworks that explicitly consider ecological boundaries across which spillover occurs. Crossing ecological boundaries involves processes that occur at many levels of organization: physiological processes at the individual level, interspecies interactions between individuals at the population level, interactions between populations of different species at the community level, and interactions between ecological communities within landscapes. Processes accelerating spillover often involve human activities such as habitat encroachment and land conversion, which are themselves ultimately driven by socioeconomic factors. In the context of Ebola and other filoviruses in Africa, we will develop the data sets, theoretical models and statistical tools needed for a general descriptive and predictive framework for spillover at ecological boundaries. Our project will follow an iterative design where results from mechanistic models are used to refine patterns that we test for empirically, and statistical models of large-scale data allow us to more realistically parameterize mechanistic models. Our work will test the generality of specific theories that so far have been applied only to a limited number of study systems. For example, ours will be among the first attempts to test the influence of Schmalhausen’s law -- an evolutionary theory that may explain the tendency for large outbreaks to occur at the edges of species ranges or during unusual weather conditions and which to date has primarily been investigated in the context of malaria -- in pathogens that rely on direct transmission. This work will demonstrate how new methods can provide unifying insight into patterns in critically important disease transmission systems and will enhance our ability to predict spillover of both filoviruses and many other zoonotic pathogens. Note that no human subjects, biohazards, or select agents will be involved in this project.