A geographical information system model to define COVID-19 problem areas with an analysis in the socio-economic context at the regional scale in the North of Spain

The work presented concerns the spatial behaviour of coronavirus disease 2019 (COVID-19) at the regional scale and the socio-economic context of problem areas over the 2020-2021 period. We propose a replicable geographical information systems (GIS) methodology based on geocodification and analysis o...

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Bibliographic Details
Main Authors: Cantarero-Prieto, D. (Author), Castillo-Salcines, V.N (Author), De Cos, O. (Author)
Format: Article
Language:English
Published: NLM (Medline) 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02266nam a2200289Ia 4500
001 10.4081-gh.2022.1067
008 220706s2022 CNT 000 0 und d
020 |a 19707096 (ISSN) 
245 1 0 |a A geographical information system model to define COVID-19 problem areas with an analysis in the socio-economic context at the regional scale in the North of Spain 
260 0 |b NLM (Medline)  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.4081/gh.2022.1067 
520 3 |a The work presented concerns the spatial behaviour of coronavirus disease 2019 (COVID-19) at the regional scale and the socio-economic context of problem areas over the 2020-2021 period. We propose a replicable geographical information systems (GIS) methodology based on geocodification and analysis of COVID-19 microdata registered by health authorities of the Government of Cantabria, Spain from the beginning of the pandemic register (29th February 2020) to 2nd December 2021. The spatial behaviour of the virus was studied using ArcGIS Pro and a 1x1 km vector grid as the homogeneous reference layer. The GIS analysis of 45,392 geocoded cases revealed a clear process of spatial contraction of the virus after the spread in 2020 with 432 km2 of problem areas reduced to 126.72 km2 in 2021. The socio-economic framework showed complex relationships between COVID-19 cases and the explanatory variables related to household characteristics, socio-economic conditions and demographic structure. Local bivariate analysis showed fuzzier results in persistent hotspots in urban and peri-urban areas. Questions about ‘where, when and how’ contribute to learning from experience as we must draw inspiration from, and explore connections to, those confronting the issues related to the current pandemic. 
650 0 4 |a COVID-19 
650 0 4 |a epidemiology 
650 0 4 |a geographic information system 
650 0 4 |a Geographic Information Systems 
650 0 4 |a human 
650 0 4 |a Humans 
650 0 4 |a pandemic 
650 0 4 |a Pandemics 
650 0 4 |a Socioeconomic Factors 
650 0 4 |a socioeconomics 
650 0 4 |a Spain 
700 1 |a Cantarero-Prieto, D.  |e author 
700 1 |a Castillo-Salcines, V.N.  |e author 
700 1 |a De Cos, O.  |e author 
773 |t Geospatial health