Revealing institutional vulnerabilities in Nordic health systems through multidimensional scaling of COVID-19 mortality data

This study introduces a novel application of Multi-Dimensional Scaling (MDS) to examine COVID-19 mortality trends across Nordic welfare states, addressing a significant gap in pandemic analysis. While existing literature has extensively compared Nordic COVID-19 responses through traditional epidemiological metrics, no previous study has employed MDS to visualize and analyze time-series mortality patterns in relation to institutional welfare structures. Drawing on excess mortality data from 2020 through 2024, this research reveals distinct national trajectories: Sweden experienced sharp increases in deaths and major outbreaks, Finland showed a steady decline, and Norway exhibited irregular patterns. The study’s methodological innovation lies in linking these MDS-derived patterns to varying degrees of market-oriented reforms across the Nordic welfare states, providing new insights into how institutional design shapes pandemic resilience. Excess mortality is measured using the P-score, which represents the percentage difference between observed and expected deaths based on pre-pandemic averages. Peak P-scores–3387.09% in Sweden (2020), 913.23% in Finland (2022), and 629.8% in Norway (2022) highlight the differing capacities of each system to respond to crises. This work fills a critical methodological gap by demonstrating how dimensionality reduction techniques can reveal institutional vulnerabilities in welfare systems during prolonged public health emergencies, offering new analytical tools for comparative welfare state research and pandemic preparedness planning.