Spatial clustering behaviour of Covid-19 conditioned by the development level: Case study for the administrative units in Romania

被引:4
作者
Cioban, Stefana [1 ,2 ]
Mare, Codruta [1 ,2 ]
机构
[1] Babes Bolyai Univ, Fac Econ, Dept Stat Forecasts Math, Business Adm, 58-60, Teodor Mihali str, Cluj-napoca 400591, Romania
[2] Babes Bolyai Univ, Interdisciplinary Ctr Data Sci, 68, Avram Iancu str, 4th floor, Cluj-napoca 400083, Cluj, Romania
关键词
Covid-19; cases; Spatial clustering; Romanian administrative units; Moran's I; Local human development index; Unemployment;
D O I
10.1016/j.spasta.2021.100558
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Spatial analyses related to Covid-19 have been so far conducted at county, regional or national level, without a thorough assessment at the continuous local level of administrative-territorial units like cities, towns, or communes. To address this gap, we employ daily data on the infection rate provided for Romanian administrative units from March to May 2021. Using the global and local Moran I spatial autocorrelation coefficients, we identify significant clustering processes in the Covid-19 infection rate. Additional analysis based on spatially smoothed rate maps and spatial regressions prove that this clustering pattern is influenced by the development level of localities, proxied by unemployment rate and Local Human Development Index. Results show the features of the 3rd wave in Romania, characterized by a quadratic trend. (C) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页数:13
相关论文
共 31 条
[1]  
Ahmadi Ali, 2020, Med J Islam Repub Iran, V34, P27, DOI 10.34171/mjiri.34.27
[2]   Analyzing the spatial determinants of local Covid-19 transmission in the United States [J].
Andersen, Lauren M. ;
Harden, Stella R. ;
Sugg, Margaret M. ;
Runkle, Jennifer D. ;
Lundquist, Taylor E. .
SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 754
[3]  
[Anonymous], 2006, URBANA
[4]   LOCAL INDICATORS OF SPATIAL ASSOCIATION - LISA [J].
ANSELIN, L .
GEOGRAPHICAL ANALYSIS, 1995, 27 (02) :93-115
[5]  
Anselin L., 2011, GMM estimation of spatial error autocorrelation with and without heteroskedasticity
[6]  
Balint C., 2021, COVID 19 ROMANIAN EC
[7]   A spatio-temporal model based on discrete latent variables for the analysis of COVID-19 incidence [J].
Bartolucci, Francesco ;
Farcomeni, Alessio .
SPATIAL STATISTICS, 2022, 49
[8]  
Cioban s, 2021, COVID 19 SPATIAL ANA
[9]  
Cristea M., 2017, MAGNET CITIES MIGRAT, P494
[10]  
De Kadt J., 2020, MAPPING VULNERABILIT, DOI DOI 10.36634/COFK6757