Evidence map›Paper›PMID 33750493›Full record

SynthesisDisaster medicine and public health preparedness2022

Regional Differences in Mortality Rates During the COVID-19 Epidemic in Italy.

Danila Azzolina, Giulia Lorenzoni, Luciano Silvestri, Ilaria Prosepe, Paola Berchialla, Dario Gregori

Open access · hybridAbstract readMeta-Analysis
In one paragraph

Synthesis in Disaster medicine and public health preparedness, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.7field-weighted citation impact, top 13% of its field
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

14 citing papers in PubMed, 28 citations in OpenAlex.

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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

6 authors at 3 institutions in 1 country.

Danila AzzolinaUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, Italy.
Giulia LorenzoniUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, Italy.
Luciano SilvestriUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, Italy.
Ilaria ProsepeUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, Italy.
Paola BerchiallaDepartment of Clinical and Biological Sciences, University of Turin, Turin, Italy.
Dario GregoriUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, Italy.ORCID 0000-0001-7906-0580
University of Padua · ITUniversità degli Studi del Piemonte Orientale “Amedeo Avogadro” · ITUniversity of Turin · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe coronavirus disease 2019 (COVID-19) outbreak started in Italy on February 20, 2020, and has resulted in many deaths and intensive care unit (ICU) admissions. This study aimed to illustrate the epidemic COVID-19 growth pattern in Italy by considering the regional differences in disease diffusion during the first 3 mo of the epidemic.

methodsOfficial COVID-19 data were obtained from the Italian Civil Protection Department of the Council of Ministers Presidency. The mortality and ICU admission rates per 100,000 inhabitants were calculated at the regional level and summarized by means of a Bayesian multilevel meta-analysis. Data were retrieved until April 21, 2020.

resultsThe highest cumulative mortality rates per 100 000 inhabitants were observed in northern Italy, particularly in Lombardia (85.3; 95% credibility intervals [CI], 75.7-94.7). The difference in the mortality rates between northern and southern Italy increased over time, reaching a difference of 67.72 (95% CI, 66-67) cases on April 2, 2020.

conclusionsNorthern Italy showed higher and increasing mortality rates during the first 3 mo of the epidemic. The uncontrolled virus circulation preceding the infection spreading in southern Italy had a considerable impact on system burnout. This experience demonstrates that preparedness against the pandemic is of crucial importance to contain its disruptive effects.

Indexed as

COVID-19Bayes TheoremDisease OutbreaksHumansItalyMortalityPandemicsCOVID-19hospitalizationICUlag effectmortality rate

Identifiers

PMID33750493
PMCPMC7985634
OpenAlexW3117762677

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.