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https://hdl.handle.net/11000/34139
Usefulness of open data to determine the incidence of COVID-19 and its relationship with atmospheric variables in Spain during the 2020 lockdown
Title: Usefulness of open data to determine the incidence of COVID-19 and its relationship with atmospheric variables in Spain during the 2020 lockdown |
Authors: Zubcoff, Jose Olcina, Jorge Morales, Javier Mazón, Jose-Norberto Mayoral, Asunción |
Editor: Elsevier |
Department: Departamentos de la UMH::Estadística, Matemáticas e Informática |
Issue Date: 2023-01 |
URI: https://hdl.handle.net/11000/34139 |
Abstract:
The SARS-CoV-2 pandemic and the spread of the COVID-19 disease led to a lockdown being imposed in Spain to
minimise contagion from 16 March 2020 to 1 May 2020. Over this period, measures were taken to reduce
population mobility (a key factor in disease transmission). The scenario thus created enabled us to examine the
impact of factors other than mobility (in this case, meteorological conditions) on the incidence of the disease, and
thus to identify which environmental variables played the biggest role in the pandemic's evolution. Worthy of
note, the data required to perform the study was entirely extracted from governmental open data sources. The
present work therefore demonstrates the utility of such data to conduct scientific research of interest to society,
leading to studies that are also fully reproducible. The results revealed a relationship between temperatures and
the spread of COVID-19. The trend was that of a slightly lower disease incidence as the minimum temperature
rises, i.e. the lower the minimum temperature, the greater the number of cases. Furthermore, a link was found
between the incidence of the disease and other variables, such as altitude and proximity to the sea. There were no
indications, however, in the study's data, of a relationship between incidence and precipitation or wind.
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Keywords/Subjects: COVID-19 Incidence Atmospheric variables Lockdown Confinement Open data |
Knowledge area: CDU: Ciencias puras y naturales: Matemáticas |
Type of document: info:eu-repo/semantics/article |
Access rights: info:eu-repo/semantics/openAccess |
DOI: https://doi.org/10.1016/j.techfore.2022.122108 |
Appears in Collections: Artículos Estadística, Matemáticas e Informática
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