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   <dc:title>Mathematical Modeling, Analysis and Simulation of COVID Transmission Epidemy under Intensive Care Units Control Strategy Using Qualitative Causal Diagrams.</dc:title>
   <dc:creator>Fernández-de-Cañete-Rodríguez, Francisco Javier</dc:creator>
   <dc:creator>Samper, Isabel</dc:creator>
   <dc:creator>García-Moral, Inmaculada</dc:creator>
   <dc:subject>COVID-19 - Modelos matemáticos</dc:subject>
   <dc:subject>Unidades de cuidados intensivos</dc:subject>
   <dc:subject>Causal Diagrams</dc:subject>
   <dc:subject>Epidemic Control</dc:subject>
   <dc:subject>Intensive Care Units</dc:subject>
   <dc:subject>Qualitative Modelling</dc:subject>
   <dc:description>The pandemic situation caused by COVID-19 has been one of the greatest problems faced by&#xd;
the world population in recent years. The use of mathematical models and computer simulation&#xd;
techniques have become very important in the study of the spread of infectious diseases. In this&#xd;
paper, a qualitative model of a proportional-integral-derivative (PID) control system for&#xd;
intensive care unit (ICU) beds occupancy in a COVID-19 epidemic situation was performed to&#xd;
prevent ICUs from saturation. A SIR-type (Susceptible/Infected/Recovered) qualitative model&#xd;
based on the causal influence diagrams is used to describe the dynamics of the pandemic&#xd;
adjusted to the behavior in space and time of COVID-19. The proposed control system used the&#xd;
demanded quantity of ICU beds as feedback signal to generate a decision policy as control&#xd;
action and simulation results show the practical feasibility and good performance of the&#xd;
proposed control system to prevent from collapse of ICUs based on social distancing and&#xd;
confinement.</dc:description>
   <dc:description>Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech</dc:description>
   <dc:date>2024-07-09T11:58:35Z</dc:date>
   <dc:date>2024-07-09T11:58:35Z</dc:date>
   <dc:date>2024</dc:date>
   <dc:type>conference output</dc:type>
   <dc:identifier>https://hdl.handle.net/10630/32012</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:relation>International Conference on Computational Mathematics, Complex Systems and Statistics (ICCMCSS-2024)</dc:relation>
   <dc:relation>Budapest (Hungria)</dc:relation>
   <dc:relation>10/05/2024</dc:relation>
   <dc:rights>open access</dc:rights>
   <dc:format>application/pdf</dc:format>
</oai_dc:dc>
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