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

Stefana Cioban; Codruta Mare

doi:10.1016/j.spasta.2021.100558

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

Spat Stat. 2022 Jun:49:100558. doi: 10.1016/j.spasta.2021.100558. Epub 2021 Dec 2.

Authors

Stefana Cioban^{1

2}, Codruta Mare^{1

2}

Affiliations

¹ Babes-Bolyai University, Faculty of Economics and Business Administration, Department of Statistics-Forecasts-Mathematics, 58-60, Teodor Mihali str., 400591, Cluj-Napoca, Romania.
² Babeş-Bolyai University, Interdisciplinary Centre for Data Science, 68, Avram Iancu str., 400083, 4th floor, Cluj-Napoca, Romania.

Abstract

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.

Keywords: Covid-19 cases; Local human development index; Moran’s I; Romanian administrative units; Spatial clustering; Unemployment.