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Capturing the Effects of Transportation on the Spread of COVID-19 with a Multi-Networked SEIR Model
In this paper 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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- PAR ID:
- 10228711
- Date Published:
- Journal Name:
- IEEE Control Systems Letters
- ISSN:
- 2475-1456
- Page Range / eLocation ID:
- 1 to 1
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/LCSYS.2021.3050954
