Modeling risk perception, vector-borne diseases, and environmental integrity: Understanding environmental impacts of policy decisions for vector control
This team will address novel questions about the feedbacks among actual disease risks, public demand for vector control, and environmental degradation. They propose to integrate perspectives from network science, physics, computer science, mathematics, social psychology, epidemiology, medical geography, vector ecology, and environmental science to study how communication within social networks shapes public understanding of the risks from both vector-borne diseases and the environmental contamination/degradation that results from control strategies. Each of these fields has its own set of specialized modeling tools to explore emergent properties of self-organizing systems. The team will focus specifically on models from network science, topology, and epidemiology using ordinary differential equations, game theory, difference equations, and numerical simulation.
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