Using a genetic algorithm to fit parameters of a COVID-19 SEIR model for US states

BACKGROUND: A Susceptible–Exposed–Infected–Removed​ (SEIR) model was developed to forecast the spread of the novel coronavirus (SARS-CoV-2) in the United States and the implications of re-opening and hospital resource utilization. The model relies on the specification of various parameters that char...

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Detalles Bibliográficos
Autor principal: Yarsky, P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. 2021
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881743/
https://www.ncbi.nlm.nih.gov/pubmed/33612959
http://dx.doi.org/10.1016/j.matcom.2021.01.022

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881743/
https://www.ncbi.nlm.nih.gov/pubmed/33612959
http://dx.doi.org/10.1016/j.matcom.2021.01.022

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