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               <mods:name>
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                  <mods:namePart>Català Sabaté, Martí</mods:namePart>
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               <mods:name>
                  <mods:role>
                     <mods:roleTerm type="text">author</mods:roleTerm>
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                  <mods:namePart>Cardona Iglesias, Pere Joan</mods:namePart>
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               <mods:name>
                  <mods:role>
                     <mods:roleTerm type="text">author</mods:roleTerm>
                  </mods:role>
                  <mods:namePart>Prats Soler, Clara</mods:namePart>
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               <mods:name>
                  <mods:role>
                     <mods:roleTerm type="text">author</mods:roleTerm>
                  </mods:role>
                  <mods:namePart>Alonso Muñoz, Sergio</mods:namePart>
               </mods:name>
               <mods:name>
                  <mods:role>
                     <mods:roleTerm type="text">author</mods:roleTerm>
                  </mods:role>
                  <mods:namePart>Álvarez Lacalle, Enrique</mods:namePart>
               </mods:name>
               <mods:name>
                  <mods:role>
                     <mods:roleTerm type="text">author</mods:roleTerm>
                  </mods:role>
                  <mods:namePart>Marchena Angos, Miquel</mods:namePart>
               </mods:name>
               <mods:name>
                  <mods:role>
                     <mods:roleTerm type="text">author</mods:roleTerm>
                  </mods:role>
                  <mods:namePart>Conesa Ortega, David</mods:namePart>
               </mods:name>
               <mods:name>
                  <mods:role>
                     <mods:roleTerm type="text">author</mods:roleTerm>
                  </mods:role>
                  <mods:namePart>López Codina, Daniel</mods:namePart>
               </mods:name>
               <mods:originInfo>
                  <mods:dateIssued encoding="iso8601">2020-07-01</mods:dateIssued>
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               <mods:abstract>The present report aims to provide a comprehensive picture of the pandemic situation of COVID-19 in the&#xd;
EU countries, and to be able to foresee the situation in the next coming days.&#xd;
We employ an empirical model, verified with the evolution of the number of confirmed cases in previous&#xd;
countries where the epidemic is close to conclude, including all provinces of China. The model does not&#xd;
pretend to interpret the causes of the evolution of the cases but to permit the evaluation of the quality of&#xd;
control measures made in each state and a short-term prediction of trends. Note, however, that the effects&#xd;
of the measures’ control that start on a given day are not observed until approximately 7-10 days later.&#xd;
The model and predictions are based on two parameters that are daily fitted to available data:&#xd;
&#xd;
a: the velocity at which spreading specific rate slows down; the higher the value, the better the&#xd;
control.&#xd;
K: the final number of expected cumulated cases, which cannot be evaluated at the initial stages&#xd;
because growth is still exponential.&#xd;
&#xd;
We show an individual report with 8 graphs and a table with the short-term predictions for different&#xd;
countries and regions. We are adjusting the model to countries and regions with at least 4 days with more&#xd;
than 100 confirmed cases and a current load over 200 cases. The predicted period of a country depends on&#xd;
the number of datapoints over this 100 cases threshold, and is of 5 days for those that have reported more&#xd;
than 100 cumulated cases for 10 consecutive days or more. For short-term predictions, we assign higher&#xd;
weight to last 3 points in the fittings, so that changes are rapidly captured by the model. The whole&#xd;
methodology employed in the inform is explained in the last pages of this document.&#xd;
In addition to the individual reports, the reader will find an initial dashboard with a brief analysis of the&#xd;
situation in EU-EFTA-UK countries, some summary figures and tables as well as long-term predictions for&#xd;
some of them, when possible. These long-term predictions are evaluated without different weights to datapoints. We also discuss a specific issue every day.These reports are funded by the European Commission (DG CONNECT, LC-01485746)
PJC and MC received funding from “la Caixa” Foundation (ID 100010434), under agreement
LCF/PR/GN17/50300003; CP, DL, SA, MC, received funding from Ministerio de Ciencia,
Innovación y Universidades and FEDER, with the project PGC2018-095456-B-I00Postprint (published version)</mods:abstract>
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               <mods:accessCondition type="useAndReproduction">http://creativecommons.org/licenses/by-nc-nd/3.0/es/ Open Access Attribution-NonCommercial-NoDerivs 3.0 Spain</mods:accessCondition>
               <mods:subject>
                  <mods:topic>Àrees temàtiques de la UPC::Ciències de la salut</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>COVID-19 (Disease)</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Coronaviruses</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Diseases -- Mathematical models</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Pandemics -- Prevention and control</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>SARS (Disease)</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Covid-19</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Pandèmies -- Predicció</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>COVID-19 (Malaltia)</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Epidèmies -- Predicció</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Epidemiologia -- Model matemàtics</mods:topic>
               </mods:subject>
               <mods:titleInfo>
                  <mods:title>Analysis and prediction of COVID-19 for EU-EFTA-UK and other countries</mods:title>
               </mods:titleInfo>
               <mods:genre>External research report</mods:genre>
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