Fractional-Order SIR Epidemic Model for Transmission Prediction of COVID-19 Disease
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In this paper, the fractional-order generalization of the susceptible-infected-recovered (SIR) epidemic model for predicting the spread of the COVID-19 disease is presented. The time-domain model implementation is based on the fixed-step method using the nabla fractional-order difference defined by Grünwald-Letnikov formula. We study the influence of fractional order values on the dynamic properties of the proposed fractional-order SIR model. In modeling the COVID-19 transmission, the model’s parameters are estimated while using the genetic algorithm. The model prediction results for the spread of COVID-19 in Italy and Spain confirm the usefulness of the introduced methodology.
2020 ◽
Vol 64
(1-2)
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pp. 615-633
2014 ◽
Vol 236
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pp. 184-194
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2020 ◽
pp. 2050071
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2013 ◽
Vol 06
(06)
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pp. 1350041