dc.contributor
Universitat Politècnica de Catalunya. Departament de Física
dc.contributor
Universitat Politècnica de Catalunya. BIOCOM-SC - Grup de Biologia Computacional i Sistemes Complexos
dc.contributor.author
Prats Soler, Clara
dc.contributor.author
Alonso Muñoz, Sergio
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Álvarez Lacalle, Enrique
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Marchena Angos, Miquel
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López Codina, Daniel
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Català Sabaté, Martí
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Cardona Iglesias, Pere Joan
dc.date.issued
2020-04-21
dc.identifier
Prats Soler, C. [et al.]. "Analysis and prediction of COVID-19 for EU-EFTA-UK and other countries". 2020.
dc.identifier
https://hdl.handle.net/2117/184420
dc.description.abstract
The present report aims to provide a comprehensive picture of the pandemic situation of COVID‐19 in the
EU countries, and to be able to foresee the situation in the next coming days.
We employ an empirical model, verified with the evolution of the number of confirmed cases in previous
countries where the epidemic is close to conclude, including all provinces of China. The model does not
pretend to interpret the causes of the evolution of the cases but to permit the evaluation of the quality of
control measures made in each state and a short-term prediction of trends. Note, however, that the effects
of the measures’ control that start on a given day are not observed until approximately 7-10 days later.
The model and predictions are based on two parameters that are daily fitted to available data:
a: the velocity at which spreading specific rate slows down; the higher the value, the better the control.
K: the final number of expected cumulated cases, which cannot be evaluated at the initial stages because growth is still exponential.
We show an individual report with 8 graphs and a table with the short-term predictions for different
countries and regions. We are adjusting the model to countries and regions with at least 4 days with more
than 100 confirmed cases and a current load over 200 cases. The predicted period of a country depends on
the number of datapoints over this 100 cases threshold, and is of 5 days for those that have reported more
than 100 cumulated cases for 10 consecutive days or more. For short-term predictions, we assign higher
weight to last 3 points in the fittings, so that changes are rapidly captured by the model. The whole
methodology employed in the inform is explained in the last pages of this document.
In addition to the individual reports, the reader will find an initial dashboard with a brief analysis of the
situation in EU-EFTA-UK countries, some summary figures and tables as well as long-term predictions for
some of them, when possible. These long-term predictions are evaluated without different weights to datapoints.
We also discuss a specific issue every day.
dc.description.abstract
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-I00
dc.description.abstract
Postprint (author's final draft)
dc.format
application/pdf
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application/pdf
dc.relation
Daily Report; 38
dc.relation
https://biocomsc.upc.edu/en/covid-19/daily-report
dc.relation
info:eu-repo/grantAgreement/EC/H2020/DGCONNECT/LC-01485746
dc.relation
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-095456-B-I00/ES/COMPUTATIONAL MODELLING OF BIOPHYSICAL PROCESSES AT MULTIPLE SCALES/
dc.relation
info:eu-repo/grantAgreement/SPAIN/LCF/PR/GN17/50300003
dc.rights
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights
Attribution-NonCommercial-NoDerivs 3.0 Spain
dc.subject
Àrees temàtiques de la UPC::Ciències de la salut
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SARS (Disease)
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Pandemics--prevention & control
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Diseases--Mathematical models
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COVID-19 (Disease)
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Models matemàtics
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Epidemiologia -- Models matemàtics
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Epidèmies -- Predicció
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COVID-19 (Malaltia)
dc.title
Analysis and prediction of COVID-19 for EU-EFTA-UK and other countries
dc.type
External research report