TY - JOUR
T1 - Studiul ecologic al vulnerabilității la COVID-19 in Serbia – utilizarea analizei hot-spot pentru elaborarea unei politici de sănătate ținând cont de caracteristicile populației
AU - Lović Obradović, Suzana
AU - Matović, Stefana
AU - Rabiei-Dastjerdi, Hamidreza
AU - Matthews, Stephen A.
N1 - Funding Information:
The research in the paper was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia; Hamidreza Rabiei-Dastjerdi is a Marie Skłodowska-Curie Career-FIT Fellow at the UCD School of Computer Science and CeADAR (Ireland's National Centre for Applied Data Analytics & AI). Career-FIT has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713654.
Publisher Copyright:
© 2022 University of Craiova, Faculty of Social Sciences, Department of Geography. All rights reserved.
PY - 2022/6
Y1 - 2022/6
N2 - The risk of severe illness or death from COVID-19 is associated with specific demographic characteristics or composition of the population within geographic areas, and the spatial relationship between these areas. The aim of this paper is to identify areas with a higher concentration of population vulnerable to COVID-19, relying on the concept of spatial dependence. Hence, we focus on the share of vulnerable populations using several salient proxy measures at municipality level data for Serbia. The degree of vulnerability at the municipality level was determined by hotspot analysis, specifically the Getis-Ord Gi* statistics. The results indicate heterogeneity in the spatial patterning and typologies of clusters across Serbia. This spatial heterogeneity reveals potentially differing degrees of risk across municipalities. The results can inform decision-makers in the fight against COVID-19 by helping to identify those areas with vulnerable populations that if exposed may stress the local health care system.
AB - The risk of severe illness or death from COVID-19 is associated with specific demographic characteristics or composition of the population within geographic areas, and the spatial relationship between these areas. The aim of this paper is to identify areas with a higher concentration of population vulnerable to COVID-19, relying on the concept of spatial dependence. Hence, we focus on the share of vulnerable populations using several salient proxy measures at municipality level data for Serbia. The degree of vulnerability at the municipality level was determined by hotspot analysis, specifically the Getis-Ord Gi* statistics. The results indicate heterogeneity in the spatial patterning and typologies of clusters across Serbia. This spatial heterogeneity reveals potentially differing degrees of risk across municipalities. The results can inform decision-makers in the fight against COVID-19 by helping to identify those areas with vulnerable populations that if exposed may stress the local health care system.
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U2 - 10.5775/fg.2022.103.i
DO - 10.5775/fg.2022.103.i
M3 - Article
AN - SCOPUS:85147652623
SN - 1583-1523
VL - 21
SP - 71
EP - 82
JO - Forum Geografic
JF - Forum Geografic
IS - 1
ER -