Linking ecological variation to parasite transmission via host movement, behavior and social networks

社会互动、社交网络和个人行为极有可能影响传染病在人类和其他社会有机体中的传播，但这些因素对疾病传播的影响程度仍然知之甚少。该项目利用易于操纵的宿主-寄生虫相互作用来阐明这些影响，因此具有显着的社会效益。最近埃博拉病毒的爆发和新传染病的不断出现强调了了解疾病传播如何受到行为和社交网络影响的重要性。 与不同机构和非政府组织建立联系将使调查人员能够分享他们的结果，为人类和野生动物健康领域提供信息。一系列的国家和国际研讨会将使研究人员能够传播他们新颖的实验和建模方法。一个无代码的图形模拟平台正在开发中，该平台将允许各级学生研究个人行为，运动，种间相互作用和资源可用性如何影响疾病传播。该平台将通过讲习班向没有计算机编码经验的个人教授，并将开发该平台的简单版本供中学班级使用。博士后研究人员，研究生和本科生将接受严格的实地和建模研究培训，并有明确的计划从服务不足的群体中招收学生。该研究利用了美国和澳大利亚研究人员之间的强大国际合作，并得到了NSF国际科学和工程办公室的共同支持。该项目利用了一个经过充分研究的蜥蜴-蜱系统，以研究生态和社会环境中的时空变化如何与宿主行为类型的个体差异相互作用，从而影响个体宿主运动，宿主社交网络和寄生虫传播。虽然这些概念上的联系是单独的简单化，每个环节和他们的相互作用提出的复杂性，需要新的实验和建模方法。实地研究将使用栖息地调查来量化蜥蜴资源和避难所的位置，并将跟踪研究地点的所有蜥蜴，以记录它们的运动，空间使用，社会互动和行为倾向。取样还将量化每只蜥蜴携带的蜱虫数量。这些研究将通过一项独特的实验来补充，该实验将遗传上不同的蜱虫添加到自由放养的蜥蜴中。该实验将量化蜥蜴宿主在寄生虫抗性方面的个体差异，具有不同行为倾向的个体作为传播实验释放的寄生虫的管道的相对能力，以及寄生虫负荷增加改变宿主行为，运动模式和社会互动的程度。 经验结果将被整合到贝叶斯统计模型和基于个人的模拟模型中，以测试行为机制在解释寄生虫负荷和传播中的作用。 然后，这些模型将用于研究环境变化，如土地使用制度的变化或气候变化将如何影响宿主-寄生虫动态。

Social interactions, social networks, and individual behavior are highly likely to influence infectious disease spread in humans and other social organisms, but the extent to which disease transmission is affected by these factors remains poorly known. This project capitalizes on a readily manipulated host-parasite interaction to elucidate these effects and therefore has significant societal benefits. The recent outbreak of Ebola and the continued emergence of new infectious diseases underscore the importance of understanding how disease transmission is affected by behavior and social networks. Established contacts with diverse agencies and non-governmental organizations will allow the investigators to share their results to inform the fields of both human and wildlife health. A series of national and international workshops will allow the investigators to disseminate their novel experimental and modeling methods. A code-free, graphical simulation platform is under development that will allow students at all levels to investigate how individual behavior, movement, interspecific interactions, and resource availability affect disease spread. This platform will be taught to individuals with no computer coding experience through workshops, and simpler versions of this platform will be developed for use in secondary school classes. Postdoctoral researchers, graduate students, and undergraduate students will be trained in rigorous field and modeling research, with clear plans to recruit students from under-served groups. The research leverages a strong international collaboration between US and Australian researchers, and is jointly supported by NSF's International Science and Engineering Office.The project takes advantage of a well-studied lizard-tick system to examine how spatial and temporal variation in the ecological and social environments interact with individual differences in host behavioral type to influence individual host movements, host social networks and parasite transmission. While these conceptual links are individually simplistic, each link and their interactions present complexities that require new experimental and modeling approaches. Field research will use habitat surveys to quantify the location of lizard resources and refuges and will track all lizards in a study site to document their movements, space-use, social interactions, and their behavioral tendencies. Sampling will also quantify the number of ticks carried by each lizard. These studies will be complemented by a unique experiment that adds genetically distinct ticks to free-ranging lizards. The experiment will quantify individual differences among lizard hosts in parasite resistance, the relative ability of individuals with different behavioral tendencies to serve as conduits for spreading experimentally-released parasites, and the extent to which increased parasite loads alter host behavior, movement patterns and social interactions. Empirical results will be integrated in Bayesian statistical models and individual-based simulation models to test the role of behavioral mechanisms in explaining parasite loads and transmission. The models will then be used to examine how environmental changes such as shifts in land use regimes or climate alterations will influence host-parasite dynamics.