Epidemic Spreading on Networks
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During the past two decades, network scientists have demonstrated that interaction among population members can dramatically influence spreading dynamics. In networked epidemic models, interactions among individuals are explicitly modeled using a contact network where individuals are the nodes, and possible interactions are the edges of the graph. This talk introduces the generalized epidemic modeling framework (GEMF) that facilitates systematic implementation of a broad spectrum of stochastic spreading processes over complex networks. GEMF is flexible and scalable to incorporate multiple nodal states and multiple types of interactions between nodes. A simple-to-use tool, GEMFsim, can numerically simulate any stochastic GEMF-based model. GEMFsim is also highly flexible and scalable due to its optimized data structure. The procedure required for setting up a simulation is simple and systematic and is available in popular programming platforms such as C, Python, R, and MATLAB.
Zoom: https://arizona.zoom.us/j/96503157705 Password: “arizona” (all lower case)