Vector Movement and Disease Risk: When Do We Need to Explicitly Account for Vector Behavior and Spatial Patterns in disease models?

许多昆虫在以植物和其他动物为食时传播疾病。然而，我们对它们的活动如何影响疾病传播知之甚少。这项研究将把昆虫行为的测量与疾病风险的数学模型结合起来，并预测疾病传播可能如何对环境变化做出反应。除了与其他科学家分享他们的成果外，研究人员还将在雪松溪长期生态研究站点(CDR)的世界级教育项目中培训K-12教师，并为7-16年级的学生开发关于疾病的教学模块。研究人员还将与CDR的NSF尊重项目合作，让美国原住民学生参与生态研究。该项目将促进生物学家和数学家之间的互动，以及研究疾病和昆虫行为的研究人员之间的互动。运动与疾病之间的相互作用日益被认为是运动生态学和传染病生态学领域的新兴前沿。对于由昆虫传播的病原体来说，昆虫媒介的移动是感染过程的关键组成部分。然而，在大多数生态疾病模型中，媒介行为被高度简化。更深入地了解媒介移动和觅食行为在调节种群水平的传染病风险中的作用是跨越种群、疾病和行为生态学的重要前沿。这里提出的方法结合了一种新的建模方法和一个易于处理的实验系统，并在三个部分促进了对病媒-宿主-病原体相互作用的理解。首先，该建模方法能够在病媒运动中结合上下文相关的决策，并将产生广泛的动植物系统中病原体矢量化的预期趋势。其次，拟议的实验工作将使用一个全球相关的植物病毒-蚜虫系统，该系统允许进行在其他(植物和动物)媒介疾病系统中几乎不可能进行的实验。最后，现有的现场数据将被用来测试关于病媒行为对感染的重要性的模型预测，以响应现场条件下的环境变化。通过从行为建模框架和实验上易于处理的经验系统生成预测，拟议的理论-实验配对有望对媒介行为在一系列媒介疾病的动力学中可能扮演的角色提供新的见解。

Many insects transmit disease as they feed on plants and other animals. However, we know little about how their movements affect the spread of disease. This research will combine measures of insect behavior with mathematical models of disease risk and make predictions about how disease transmission may respond to environmental change. In addition to sharing their results with other scientists, the researchers will train K-12 teachers at the world-class education program at Cedar Creek Long Term Ecological Research site (CDR), and develop teaching modules about disease for students in grades 7-16. The researchers will also partner with CDR's NSF ESTEEM project to involve Native American students in ecology research. The project will promote interaction between biologists and mathematicians, and between researchers who study disease and insect behavior. The interaction between movement and disease is increasingly recognized as an emerging frontier for both the fields of movement ecology and the ecology of infectious diseases. For pathogens transmitted by insects, insect vector movement is a key component of the infection process. Yet, in most ecological disease models, vector behavior is highly simplified. A deeper understanding of the role of vector movement and foraging behavior in mediating population-level infectious disease risk is an important frontier spanning population, disease, and behavioral ecology. The approach proposed here couples a novel modeling approach with a tractable experimental system and promotes understanding of vector-host-pathogen interactions in three parts. First, the modeling approach enables the incorporation of context-dependent decision making in vector movement and will generate expected trends for vectored pathogens in animal and plant systems, broadly. Second, the proposed experimental work will use a globally relevant phytovirus-aphid system that permits experiments that are near impossible in other (plant and animal) vectored disease systems. Finally, existing field data will be used to test model predictions about the importance of vector behavior for infection in response to environmental change under field conditions. By generating predictions from a behavioral modeling framework and an experimentally-tractable empirical system, the proposed theory-experiment pairing promises novel insights into the likely role of vector behavior in the dynamics of a wide array of vectored diseases.