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

论文研究：使用动态网络模型揭示行为和免疫能力的异质性如何影响新兴野生动物疾病的疾病动态

• 批准号: 1701069
• 负责人: Meggan Craft
• 金额: $ 1.56万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1701069&HistoricalAwards=false
• 关键词: DISSERTATION; RESEARCH; Using; dynamic; network

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.

新兴的传染病是出现在新宿主或新地方的疾病。当病原体的新菌株出现，或者是由于将病原体引入新区域时，它们可能会导致它们，并通过疾病和死亡威胁野生动植物，牲畜和人类。由于大多数转向人类的新兴传染病来自野生动植物，因此了解野生动植物疾病很重要。通常，科学家使用疾病的数学模型作为了解疾病如何传播或帮助预测未来趋势的现有模式的工具。这项研究的重点是理解宿主在其行为方式上的差异，或者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了解应将感染后发生的事物的个体差异纳入疾病模型。有了这些信息，科学家和经理将能够更好地设计数据收集和疾病模型，以控制新兴的传染病。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，包括可以在许多其他学院和大学中使用的网站。有助于野生动植物来源的新兴感染疾病的严重后果，以及在野生疾病中收集病原体数据的时间和资源密集型的性质，可用于捕获野生疾病的努力，以实现的努力，这些工具是必要的。这项研究的目的是将经验和建模方法联系起来，以更好地了解特征的宿主之间的变化如何影响野生动植物系统中的病原体传播。它将将理论模型与来自房屋雀科的宿主 - 病原体系统及其细菌病原体Mycoplasma Gallisepticum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态，还将探索感染引起的行为变化的影响。实验性甲霉菌感染数据与经验接触网络数据相结合，将用于参数化动态网络疾病模型。这项研究将提供对行为和免疫能力之间在流行动力学中协方差的潜在作用的新见解，并将成为最早将动态网络应用于野生动植物中新兴的传染病系统的模型之一。

项目成果

Disease outbreak thresholds emerge from interactions between movement behavior, landscape structure, and epidemiology

• DOI: 10.1073/pnas.1801383115
• 发表时间: 2018-07-10
• 期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• 影响因子: 11.1
• 作者: White, Lauren A.;Forester, James D.;Craft, Meggan E.
• 通讯作者: Craft, Meggan E.

Covariation between the physiological and behavioral components of pathogen transmission: host heterogeneity determines epidemic outcomes

病原体传播的生理和行为成分之间的协变：宿主异质性决定流行病结果

• DOI: 10.1111/oik.04527
• 发表时间: 2018
• 期刊: Oikos
• 影响因子: 3.4
• 作者: White, Lauren A.;Forester, James D.;Craft, Meggan E.
• 通讯作者: Craft, Meggan E.

Dynamic, spatial models of parasite transmission in wildlife: Their structure, applications and remaining challenges

• DOI: 10.1111/1365-2656.12761
• 发表时间: 2018-05-01
• 期刊: JOURNAL OF ANIMAL ECOLOGY
• 影响因子: 4.8
• 作者: White，Lauren A.;Forester，James D.;Craft，Meggan E.
• 通讯作者: Craft，Meggan E.

Comparison of Antimicrobial-Resistant Escherichia coli Isolates from Urban Raccoons and Domestic Dogs

从城市浣熊和家犬中分离出的耐药大肠杆菌的比较

• DOI: 10.1128/aem.00484-21
• 发表时间: 2021
• 期刊: Applied and Environmental Microbiology
• 影响因子: 4.4
• 作者: Worsley-Tonks, Katherine E.;Gehrt, Stanley D.;Miller, Elizabeth A.;Singer, Randall S.;Bender, Jeff B.;Forester, James D.;McKenzie, Shane C.;Travis, Dominic A.;Johnson, Timothy J.;Craft, Meggan E.
• 通讯作者: Craft, Meggan E.