Spatiotemporal clustering patterns and sociodemographic determinants of COVID-19 (SARS-CoV-2) infections in Helsinki, Finland

• DOI: 10.1016/j.sste.2022.100493
• Publication Date: 2022-02-05T15:38:17Z
• Authors: Mika Siljander; Ruut Uusitalo; Petri Pellikka; Sanna Isosomppi; Olli Vapalahti
• Keywords: 2019-20 coronavirus outbreak; Betacoronavirus

This study aims to elucidate the variations in spatiotemporal patterns and sociodemographic determinants of SARS-CoV-2 infections Helsinki, Finland. Global local spatial autocorrelation were inspected with Moran's I LISA statistics, Getis-Ord Gi* statistics was used identify hot spot areas. Space-time detect clusters high relative risk regression models implemented explain for clusters. The findings revealed presence clustering COVID-19 cases. High-high areas emerged primarily Helsinki's eastern neighborhoods, which are socioeconomically vulnerable, a few exceptions revealing outbreaks other variation rates largely explained by median income number foreign citizens population. Furthermore, use multiple analysis methods recommended gain deeper insights into complex