Analysing spatiotemporal patterns of Covid-19 confirmed deaths at the NUTS-2 regional level
Analysing spatiotemporal patterns of Covid-19 confirmed deaths at the NUTS-2 regional level

Summary/Abstract: During the ongoing Covid-19 pandemic,understanding the spatiotemporal patterns of the virus is crucial for policymakers to intervene promptly. The relevance of spatial proximity in the spread of the pandemic necessitates adequate tools, and noisy data must be properly treated. This study proposes obtaining clusters of European regions using smoothed curves of daily deaths from March2020–March 2022. A functional representation of the curves w<s implemented to extract the features used in a clustering algorithm that allows spatial proximity. In a spatial regression model, the authors also investigated the role of clusters and pre-existing conditions on cumulative deaths, and observed that air pollution, health conditions, and population age structure are significantly associated withCovid-19 confirmed deaths.

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