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<dc:title>Urban population dynamics during the COVID- 19 pandemic based on mobile phone data</dc:title>
<dc:creator>Romanillos Arroyo, Gustavo</dc:creator>
<dc:creator>García Palomares, Juan Carlos</dc:creator>
<dc:creator>Moya-Gómez, Borja</dc:creator>
<dc:creator>Gutiérrez Puebla, Javier</dc:creator>
<dc:creator>Torres, Javier</dc:creator>
<dc:creator>López, Mario</dc:creator>
<dc:creator>García Cantú Ros, Oliva</dc:creator>
<dc:creator>Herranz, Ricardo</dc:creator>
<dc:subject>COVID-19</dc:subject>
<dcterms:abstract>Because of the fast expansion of the COVID-19 pandemic in 2020, many countries&#xd;
established lockdowns, implementing different restrictions on people’s mobility. Analysing&#xd;
the effectiveness of these measures is crucial to better react to similar future scenarios. This&#xd;
research uses anonymous mobile phone data to study the impact of the Spanish lockdown&#xd;
on the daily dynamics of the Madrid metropolitan area. The analysis is focused on a&#xd;
reference week prior to the lockdown and on several weeks of the lockdown in which&#xd;
different restrictions were in place. For this timeframe, population distribution is compared&#xd;
during the day and at night and presence profiles are obtained throughout the day for each&#xd;
type of land use. In addition, a multiple regression analysis is carried out to determine the&#xd;
impact of the different land uses on the local population. The results in the reference week,&#xd;
pre-COVID-19, show how the population in activity areas increases in each time slot on a&#xd;
specific day and how in residential areas it decreases. However, during the lockdown,&#xd;
activity areas cease to attract population during the day and the residential areas therefore no&#xd;
longer show a decrease. Only basic essential commercial activities, or others that require the&#xd;
presence of workers maintain some activity during lockdown.</dcterms:abstract>
<dcterms:dateAccepted>2022-09-15T11:25:56Z</dcterms:dateAccepted>
<dcterms:available>2022-09-15T11:25:56Z</dcterms:available>
<dcterms:created>2022-09-15T11:25:56Z</dcterms:created>
<dcterms:issued>2021-07</dcterms:issued>
<dc:type>info:eu-repo/semantics/conferenceObject</dc:type>
<dc:identifier>978-84-18465-12-3</dc:identifier>
<dc:identifier>http://hdl.handle.net/10259/6864</dc:identifier>
<dc:identifier>10.36443/10259/6864</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>R-Evolucionando el transporte</dc:relation>
<dc:relation>http://hdl.handle.net/10259/6490</dc:relation>
<dc:relation>https://doi.org/10.36443/9788418465123</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098402-B-I00/ES/ANALISIS DINAMICO DE LOS PATRONES DE MOVILIDAD A PARTIR DE BIG DATA</dc:relation>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:publisher>Universidad de Burgos. Servicio de Publicaciones e Imagen Institucional</dc:publisher>
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