Abstract
The network SEIR model is a locally resolved compartment model with four populations, the susceptible, exposed, infectious, and recovered groups S, E, I, and R, at each node of the network. It characterizes the spatio-temporal spreading of infectious diseases along the edges of the network proportional to human mobility. Since the network SEIR model has no analytical solution, we discretize it in space using a weighted Laplacian graph and apply explicit and implicit time integration schemes to solve it. To illustrate the features of the network SEIR model, we simulate the early COVID-19 outbreak in the United States and the European Union using reported case data and air travel statistics. The learning objectives of this chapter on SEIR network modeling are to
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Kuhl, E. (2021). The network SEIR model. In: Computational Epidemiology. Springer, Cham. https://doi.org/10.1007/978-3-030-82890-5_10
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DOI: https://doi.org/10.1007/978-3-030-82890-5_10
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Publisher Name: Springer, Cham
Print ISBN: 978-3-030-82889-9
Online ISBN: 978-3-030-82890-5
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