A Mathematical Model of COVID-19: Analysis and Identification of Parameters for Better Decision Making

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ISSN Print: 2152-7385
ISSN Online: 2152-7393
www.scirp.org/journal/am
E-mail: am@scirp.org

"A Mathematical Model of COVID-19: Analysis and Identification of Parameters for Better Decision Making"
written by Ouaténi Diallo, Yaya Kone, Chata Sanogo, Jérôme Pousin,
published by Applied Mathematics, Vol.13 No.2, 2022

has been cited by the following article(s):

[1]	Evaluation of dynamic growth trend of renewable energy based on mathematical model
	Energy Reports, 2023

[2]	A Review of Mathematical Models of COVID-19 Transmission
	Contemporary Mathematics, 2023

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[1]	Evaluation of dynamic growth trend of renewable energy based on mathematical model Energy Reports, 2023 DOI:10.1016/j.egyr.2022.11.139

[2]	Development of a probabilistic model for Covid-19 dynamics with consideration of non-severe and severe infections Alexandria Engineering Journal, 2023 DOI:10.1016/j.aej.2023.09.067