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                <text>Coronavirus</text>
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                <text>Dominio científico: Coronavirus</text>
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              <text>Fractional-Order SIR Epidemic Model for Transmission Prediction of COVID-19 Disease</text>
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              <text>Kamil Kozioł, Rafał Stanisławski, Grzegorz Bialic</text>
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              <text>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.</text>
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              <text>2020</text>
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              <text>covid-19, SIR epidemic model, Fractional order systems</text>
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              <text>10.3390/app10238316</text>
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              <text>Epidemiology and Health</text>
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              <text>Korean Society of Epidemiology</text>
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              <text>Biology (General), Chemistry, Engineering (General). Civil engineering (General), Technology, Physics</text>
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