DISSERTATION RESEARCH: Using dynamic network models to reveal how heterogeneity in behavioral and immune competence impact disease dynamics in an emerging wildlife disease

新发传染病是指在新的宿主或新的地方出现的疾病。当出现新的病原体菌株，或病原体被引入一个新的地区时，就会产生这种疾病，并可能通过疾病和死亡威胁野生动物、牲畜和人类。因为大多数传染给人类的新发传染病都来自野生动物，所以了解野生动物疾病很重要。通常，科学家使用疾病的数学模型作为工具来了解疾病如何传播的现有模式或帮助预测未来趋势。这项研究的重点是了解宿主之间的行为差异，或者它们的身体对感染的反应如何影响疾病流行的下一步：当病原体在宿主之间传播时。这项研究将帮助科学家更好地理解感染后发生的个体差异应该如何纳入疾病模型。有了这些信息，科学家和管理人员将能够更好地设计数据收集和疾病模型，以便有针对性地控制新出现的传染病。该项目还将培训一名研究生，并为小学和本科生开发新的教学工具，包括一个可以在许多其他学院和大学使用的网站。鉴于野生动物来源的新发传染病可能造成严重后果，以及在野生动物种群中收集病原体数据的时间和资源密集性，改进的疾病模型是必要的工具，可以深入了解捕捉传播过程所需的研究工作。本研究的目的是将经验和建模方法联系起来，以更好地了解宿主间性状变化如何影响野生动物系统中病原体的传播。它将理论模型与家雀宿主-病原体系统及其细菌病原体鸡毒支原体的经验数据相结合。这项工作将解决行为和生理表型如何影响疾病动力学，也将探索感染诱导的行为改变的影响。实验数据结合经验接触网络数据将用于参数化动态网络疾病模型。这项研究将为行为和免疫能力之间的共同变异在流行病动力学中的潜在作用提供新的见解，并将作为第一个将动态网络应用于野生动物新兴传染病系统的模型之一。

Emerging infectious diseases are diseases that appear in new hosts or in a new place. They can result when new strains of a pathogen arise, or from a pathogen being introduced into a new area, and can threaten wildlife, livestock, and humans through illness and death. Because most emerging infectious diseases that shift to humans come from wildlife it is important to understand wildlife diseases. Often, scientists use mathematical models of disease as tools to understand existing patterns of how a disease spreads or to help predict future trends. This research focuses on understanding differences among hosts in how they behave, or how their bodies respond to infection affect the next step in a disease epidemic: when the pathogen spreads among hosts. This research will help scientists better understand how individual differences in what happens after infection should be incorporated into disease models. With this information, scientists and managers will be able to better design data collection and disease models for the targeted control of emerging infectious diseases. The project will also train a graduate student and result in the development of new teaching tools for grade school and undergraduate students, including a website that could be used at many other colleges and universities.Given the potential for severe consequences of emerging infections diseases with wildlife sources and the time and resource-intensive nature of gathering pathogen data in wildlife populations, improved disease models are necessary tools for providing insight into the research effort necessary to capture the transmission process. The objective of this research is to link empirical and modeling approaches to better understand how among-host variation in traits affects pathogen transmission in a wildlife system. It will integrate a theoretical model with empirical data from the host-pathogen system of house finches and their bacterial pathogen, Mycoplasma gallisepticum. This work will address how the behavioral and physiological phenotypes affect disease dynamics and will also explore the effects of infection-induced behavioral changes. Experimental M. gallisepticum infection data combined with empirical contact network data will be used to parameterize a dynamic network disease model. This research will provide novel insights into the potential role of covariation between behavioral and immune competence in epidemic dynamics, and will serve as one of the first models to apply dynamic networks to an emerging infectious disease system in wildlife.