Evidence map›Paper›PMID 37468698›Full record

ArticleScientific reports2023

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

Chiara Podrecca, Enea Parimbelli, Daniele Pala, Cindy Cheng, Luca Messerschmidt, Tim Büthe, Riccardo Bellazzi

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Chiara PodreccaDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy. chiara.podrecca01@universitadipavia.it.
Enea ParimbelliDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
Daniele PalaDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
Cindy ChengTechnical University of Munich, Munich, Germany.
Luca MesserschmidtTechnical University of Munich, Munich, Germany.
Tim BütheTechnical University of Munich, Munich, Germany.
Riccardo BellazziDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

COVID-19CyprusFranceHumansPandemicsPolicy

Identifiers

PMID37468698
PMCPMC10356910

What OpenQuestion holds

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Registered trials

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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.