Literature DB >> 35783814

Capturing the Effects of Transportation on the Spread of COVID-19 With a Multi-Networked SEIR Model.

Damir Vrabac1, Mingfeng Shang1, Brooks Butler2, Joseph Pham3, Raphael Stern3, Philip E Pare2.   

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.

Entities:  

Keywords:  COVID-19; Control applications; SEIR model; transportation networks

Year:  2021        PMID: 35783814      PMCID: PMC8545039          DOI: 10.1109/LCSYS.2021.3050954

Source DB:  PubMed          Journal:  IEEE Control Syst Lett


  5 in total

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1.  Data analytics during pandemics: a transportation and location planning perspective.

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