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 Grunwald-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
Fractional-Order SIR Epidemic Model for Transmission Prediction of COVID-19 Disease