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Spatial inequalities of COVID-19 incidence and associated socioeconomic risk factors in Portugal
Author(s) -
Ricardo Almendra,
Paula Santana,
Cláudia Costa
Publication year - 2021
Publication title -
boletín de la asociación de geógrafos españoles/boletín de la asociación de geógrafos españoles
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.374
H-Index - 19
eISSN - 2605-3322
pISSN - 0212-9426
DOI - 10.21138/bage.3160
Subject(s) - socioeconomic status , geography , context (archaeology) , incidence (geometry) , covid-19 , ordinary least squares , inequality , geographically weighted regression , psychological intervention , demography , socioeconomics , demographic economics , econometrics , statistics , medicine , population , economics , sociology , mathematics , infectious disease (medical specialty) , mathematical analysis , geometry , archaeology , disease , pathology , psychiatry
COVID-19 hit the world in a sudden and uneven way. Scientific community has provided strong evidence about socioeconomic characteristics of the territory associated with the geographical pattern of COVID-19 incidence. Still, the role played by these factors differs between study areas. Geographically Weighted Regression (GWR) models were applied to explore the spatially varying association between age-standardized COVID-19 incidence rate in 2020 and socioeconomic conditions in Portugal, at the municipality level. The spatial context was defined as a function of the number of neighbours; the bandwidth was determined through AIC. Prior, the validity of the GWR was assessed through ordinary least squares models. Border proximity, proportion of overcrowded living quarters, persons employed in manufacturing establishments and persons employed in construction establishments were found to be significant predictors. It was possible to observe that municipalities are affected differently by the same factor, and that this varying influence has identifiable geographical patterns, the role of each analysed factor varies importantly across the country. This study provides useful insights for policymakers for targeted interventions and for proper identification of risk factors.

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