Evidence map›Paper›PMID 41986502›Full record

ArticleScientific reports2026

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

Giuseppe Orlando, Michele Bufalo, Varvara Nazarova

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Giuseppe OrlandoDepartment of Economics and Finance, University of Bari, 70124, Bari, Italy. giuseppe.orlando@uniba.it.
Michele BufaloDepartment of Economics, Management and Business Law, University of Bari, 70124, Bari, Italy.
Varvara NazarovaDepartment of Finance, HSE University, 194100, Saint Petersburg, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

COVID-19FinlandHumansNorwayPandemicsSARS-CoV-2Scandinavian and Nordic CountriesSwedenCOVID-19 mortalityExcess mortalityHealth system resilienceMultidimensional scalingNordic welfare states

Identifiers

PMID41986502
PMCPMC13237384

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.