A comparative analysis of the effects of containment policies on the epidemiological manifestation of the COVID-19 pandemic across nine European countries

被引:1
|
作者
Podrecca, Chiara [1 ]
Parimbelli, Enea [1 ]
Pala, Daniele [1 ]
Cheng, Cindy [2 ]
Messerschmidt, Luca [2 ]
Buethe, Tim [2 ]
Bellazzi, Riccardo [1 ]
机构
[1] Univ Pavia, Dept Elect Comp & Biomed Engn, Pavia, Italy
[2] Tech Univ Munich, Munich, Germany
关键词
INTERVENTIONS;
D O I
10.1038/s41598-023-37751-4
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The COVID-19 pandemic has been a catastrophic event that has seriously endangered the world's population. Governments have largely been unprepared to deal with such an unprecedented calamity, partially due to the lack of sufficient or adequately fine-grained data necessary for forecasting the pandemic's evolution. To fill this gap, researchers worldwide have been collecting data about different aspects of COVID-19's evolution and government responses to them so as to provide the foundation for informative models and tools that can be used to mitigate the current pandemic and possibly prevent future ones. Indeed, since the early stages of the pandemic, a number of research initiatives were launched with this goal, including the PERISCOPE (Pan-European Response to the ImpactS of COVID-19 and future Pandemics and Epidemics) Project, funded by the European Commission. PERISCOPE aims to investigate the broad socio-economic and behavioral impacts of the COVID-19 pandemic, with the goal of making Europe more resilient and prepared for future large-scale risks. The purpose of this study, carried out as part of the PERISCOPE project, is to provide a first European-level analysis of the effect of government policies on the spread of the virus. To do so, we assessed the relationship between a novel index, the Policy Intensity Index, and four epidemiological variables collected by the European Centre for Disease Control and Prevention, and then applied a comprehensive Pan-European population model based on Multilevel Vector Autoregression. This model aims at identifying effects that are common to some European countries while treating country-specific policies as covariates, explaining the different evolution of the pandemic in nine selected countries due to data availability: Spain, France, Netherlands, Latvia, Slovenia, Greece, Ireland, Cyprus, Estonia. Results show that specific policies' effectiveness tend to vary consistently within the different countries, although in general policies related to Health Monitoring and Health Resources are the most effective for all countries.
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页数:15
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