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

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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.