Comparison between simulated scenarios and Swedish COVID-19 cases throughout the pandemic
Journal article, 2025
the following attributes: area under the curves, peak timings, and growth/decline rates before and after peaks. Rather than using an arbitrary cut-off, we used a threshold determined through Receiver Operating Characteristic (ROC) analysis, with performance evaluated using the Area Under the Curve
(AUC), based on true positives identified by visual inspection for categorization. To further evaluate SEr’s effectiveness, we conducted a sensitivity analysis across the full range of possible threshold values within the unit interval. Applying SEr with an optimal threshold determined through ROCanalysis 7 rounds out of 11 rounds were classified as having one or more similar scenarios, including the 6 rounds identified by visual inspection. Our findings indicate that, despite the challenges of a rapidly evolving epidemic, PHAS delivered simulations that reflected real-world trends in most of the rounds.
Scenario analysis
Simulation similarity
COVID-19
Time series comparison
Author
Hatef Darabi
Public Health Agency of Sweden
Ilias Galanis
Public Health Agency of Sweden
Federico Benzi
Public Health Agency of Sweden
Gerard Farre Puiggali
Public Health Agency of Sweden
Philip Gerlee
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
University of Gothenburg
Torbjorn Lundh
University of Gothenburg
Lisa Brouwers
Public Health Agency of Sweden
Scientific Reports
2045-2322 (ISSN) 20452322 (eISSN)
Vol. 15 1 23653Subject Categories (SSIF 2025)
Public Health, Global Health and Social Medicine
Computer Sciences
DOI
10.1038/s41598-025-08682-z
PubMed
40603586