A Computational Model for Estimating the Progression of COVID-19 Cases in the US West and East Coast Population Regions

The ongoing coronavirus disease 2019 (COVID-19) pandemic is of global concern and has recently emerged in the US. In this paper, we construct a stochastic variant of the SEIR model to estimate a quasi-worst-case scenario prediction of the COVID-19 outbreak in the US West and East Coast population re...

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Bibliographic Details
Published in:Experimental Results 2020-01, Vol.1, p.e41-e41, Article e41
Main Authors: Yeo, Yao-Yu, Yeo, Yao-Rui, Yeo, Wan-Jin
Format: Article
Language:English
Subjects:
Coasts
computational model
coronavirus
Coronaviruses
COVID-19
Disease transmission
Epidemics
Fatalities
Hospitals
Infections
Life Science and Biomedicine
Mathematical models
Medical personnel
Medical supplies
Novel-Result
Ordinary differential equations
SARS-CoV-2
Severe acute respiratory syndrome coronavirus 2
Simulation
viral transmission
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Summary:The ongoing coronavirus disease 2019 (COVID-19) pandemic is of global concern and has recently emerged in the US. In this paper, we construct a stochastic variant of the SEIR model to estimate a quasi-worst-case scenario prediction of the COVID-19 outbreak in the US West and East Coast population regions by considering the different phases of response implemented by the US as well as transmission dynamics of COVID-19 in countries that were most affected. The model is then fitted to current data and implemented using Runge-Kutta methods. Our computation results predict that the number of new cases would peak around mid-April 2020 and begin to abate by July provided that appropriate COVID-19 measures are promptly implemented and followed, and that the number of cases of COVID-19 might be significantly mitigated by having greater numbers of functional testing kits available for screening. The model is also sensitive to assigned parameter values and reflects the importance of healthcare preparedness during pandemics.
ISSN:2516-712X
2516-712X
DOI:10.1017/exp.2020.45