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                <text>Coronavirus</text>
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                <text>Dominio científico: Coronavirus</text>
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              <text>Least-Squares Finite Element Method for a Meso-Scale Model of the Spread of COVID-19</text>
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              <text>Fleurianne Bertrand, Emilie Pirch</text>
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              <text>This paper investigates numerical properties of a flux-based finite element method for the discretization of a SEIQRD (susceptible-exposed-infected-quarantined-recovered-deceased) model for the spread of COVID-19. The model is largely based on the SEIRD (susceptible-exposed-infected-recovered-deceased) models developed in recent works, with additional extension by a quarantined compartment of the living population and the resulting first-order system of coupled PDEs is solved by a Least-Squares meso-scale method. We incorporate several data on political measures for the containment of the spread gathered during the course of the year 2020 and develop an indicator that influences the predictions calculated by the method. The numerical experiments conducted show a promising accuracy of predictions of the space-time behavior of the virus compared to the real disease spreading data.</text>
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              <text>2021</text>
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              <text>covid-19, least-squares finite element method, susceptible-exposed-infected-quarantined-recovered-deceased (SEIQRD)</text>
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              <text>10.3390/computation9020018</text>
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              <text>Epidemiology and Health</text>
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          <name>Publisher</name>
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              <text>Korean Society of Epidemiology</text>
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          <name>Coverage</name>
          <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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              <text>Electronic computers. Computer science</text>
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