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Capturing the Effects of Transportation on the Spread of COVID-19 With a Multi-Networked SEIR Model
Damir Vrabac1, Mingfeng Shang1, Brooks Butler2
1Department of Computer ScienceStanford University 13137 Nacka Sweden.
Abstract:
In this letter we present a deterministic discrete-time networked SEIR model that includes a number of transportation networks, and present assumptions under which it is well defined. We analyze the limiting behavior of the model and present necessary and sufficient conditions for estimating the spreading parameters from data. We illustrate these results via simulation and with real COVID-19 data from the Northeast United States, integrating transportation data into the results.
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