Comparison between simulated scenarios and Swedish COVID-19 cases throughout the pandemic
Abstract This study assesses the accuracy of COVID-19 scenarios for new infections produced by the Swedish Public Health Agency (PHAS) from December 1, 2020, to March 20, 2023. We introduce a Similarity Error ( $$\:SEr$$ ), which evaluates the dissimilarity between simulated and observed case time s...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-08682-z |
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| author | Hatef Darabi Ilias Galanis Federico Benzi Gerard Farré Puiggalí Philip Gerlee Torbjörn Lundh Lisa Brouwers |
| author_facet | Hatef Darabi Ilias Galanis Federico Benzi Gerard Farré Puiggalí Philip Gerlee Torbjörn Lundh Lisa Brouwers |
| author_sort | Hatef Darabi |
| collection | DOAJ |
| description | Abstract This study assesses the accuracy of COVID-19 scenarios for new infections produced by the Swedish Public Health Agency (PHAS) from December 1, 2020, to March 20, 2023. We introduce a Similarity Error ( $$\:SEr$$ ), which evaluates the dissimilarity between simulated and observed case time series using 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 ROC-analysis 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. |
| format | Article |
| id | doaj-art-e529b04399d04bb088afaea49cf13d08 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-e529b04399d04bb088afaea49cf13d082025-08-20T03:37:27ZengNature PortfolioScientific Reports2045-23222025-07-0115111010.1038/s41598-025-08682-zComparison between simulated scenarios and Swedish COVID-19 cases throughout the pandemicHatef Darabi0Ilias Galanis1Federico Benzi2Gerard Farré Puiggalí3Philip Gerlee4Torbjörn Lundh5Lisa Brouwers6The Public Health Agency of SwedenThe Public Health Agency of SwedenThe Public Health Agency of SwedenThe Public Health Agency of SwedenMathematical Sciences, Chalmers University of Technology and University of GothenburgMathematical Sciences, Chalmers University of Technology and University of GothenburgThe Public Health Agency of SwedenAbstract This study assesses the accuracy of COVID-19 scenarios for new infections produced by the Swedish Public Health Agency (PHAS) from December 1, 2020, to March 20, 2023. We introduce a Similarity Error ( $$\:SEr$$ ), which evaluates the dissimilarity between simulated and observed case time series using 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 ROC-analysis 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.https://doi.org/10.1038/s41598-025-08682-zCOVID-19Scenario analysisSimulation similarityTime series comparison |
| spellingShingle | Hatef Darabi Ilias Galanis Federico Benzi Gerard Farré Puiggalí Philip Gerlee Torbjörn Lundh Lisa Brouwers Comparison between simulated scenarios and Swedish COVID-19 cases throughout the pandemic Scientific Reports COVID-19 Scenario analysis Simulation similarity Time series comparison |
| title | Comparison between simulated scenarios and Swedish COVID-19 cases throughout the pandemic |
| title_full | Comparison between simulated scenarios and Swedish COVID-19 cases throughout the pandemic |
| title_fullStr | Comparison between simulated scenarios and Swedish COVID-19 cases throughout the pandemic |
| title_full_unstemmed | Comparison between simulated scenarios and Swedish COVID-19 cases throughout the pandemic |
| title_short | Comparison between simulated scenarios and Swedish COVID-19 cases throughout the pandemic |
| title_sort | comparison between simulated scenarios and swedish covid 19 cases throughout the pandemic |
| topic | COVID-19 Scenario analysis Simulation similarity Time series comparison |
| url | https://doi.org/10.1038/s41598-025-08682-z |
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