A társadalmi-területi változók szerepe a COVID-19-halálozás regionális egyenlőtlenségeiben Magyarországon - Balázs Páger; Annamária Uzzoli; Csaba G. Tóth (Hungarian Academy of Sciences, Institute of Economics, Centre for Economic and Regional Studies, 2023)
– Hungary is one of the five countries in the world most affected by the pandemic in terms of registered COVID-19 mortality up to 2023. Our research aims to identify those socioeconomic variables that explain the geographical distribution of the registered district-level mortality burden of the pandemic. OLS and spatial regression analyses were applied at the sub-regional level covering 175 areas from the outbreak of the pandemic till 31 January 2022. The higher share of elderly people and the higher respiratory death rate were associated with a more severe mortality burden due to the pandemic. Districts with a higher share of the population having tertiary educational attainment tended to have lower COVID-19 mortality rates. In contrast to much of the literature's findings, variables related to healthcare access were not found to be significantly associated with district-level COVID-19 mortality. In addition, our results indicate that the spatial term of COVID-19 mortality is significant. Positive spatial autocorrelation can be observed in some less developed districts and a few inner peripheral areas where COVID19 mortality was relatively high, and relatively developed areas like the agglomeration area of the capital in which COVID-19 mortality was low.
Keywords: I14; 330; COVID-19 mortality; socio-spatial inequality; ordinary least squares (OLS); spatial autocorrelation; district