ArticleScientific reports2025
Impact of COVID-19 pandemic phases on emergency medical services reaction times in Southern Poland.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed.
- Dynamic demand forecasting and capacity assessment for emergency care system: a hybrid time series and machine learning approach with evidence from Beijing.BMC health services research · 2026Article
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Authors and funding
2 authors.
Funding
Abstract
This study analyses Emergency Medical Services (EMS) reaction times and call volumes in Małopolska, Poland, during and after the COVID-19 pandemic (2020-2023). The main objective was to evaluate healthcare system strain under different phases of the pandemic and to identify temporal patterns affecting EMS performance. Using statistical analyses, we investigated correlations between EMS call volumes and reaction times across various temporal scales, including hourly, daily, monthly, and yearly patterns. Results showed significant increases in EMS reaction times during pandemic peaks, especially during the vaccination rollout phase, correlating strongly with increased call volumes. The highest reaction delays occurred in December, weekends, and evening hours. Despite high call volumes, reaction times improved in later pandemic stages, indicating effective adaptation of EMS strategies. Seasonal and daily cyclicality in call patterns suggests opportunities for optimized resource allocation. The study highlights the resilience and adaptability of EMS systems under crisis conditions and recommends dynamic allocation strategies, accurate demand forecasting, and improved crisis communication. These findings offer critical insights for enhancing future EMS crisis management strategies and operational preparedness.
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