Evidence map›Paper›PMID 38684947›Full record

ArticleBMC infectious diseases2024

Spatial spread of COVID-19 during the early pandemic phase in Italy.

Valeria d'Andrea, Filippo Trentini, Valentina Marziano, Agnese Zardini, Mattia Manica, Giorgio Guzzetta, Marco Ajelli, Daniele Petrone, Martina Del Manso, Chiara Sacco and 6 more

Abstract read
In one paragraph

Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Valeria d'Andrea *Center for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Filippo Trentini *Center for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Valentina MarzianoCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Agnese ZardiniCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Mattia ManicaCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Giorgio GuzzettaCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Marco AjelliLaboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA.
Daniele PetroneDepartment of Infectious Diseases, Istituto Superiore Di Sanità, Rome, Italy.
Martina Del MansoDepartment of Infectious Diseases, Istituto Superiore Di Sanità, Rome, Italy.
Chiara SaccoDepartment of Infectious Diseases, Istituto Superiore Di Sanità, Rome, Italy.
Xanthi AndrianouDepartment of Infectious Diseases, Istituto Superiore Di Sanità, Rome, Italy.
Antonino BellaDepartment of Infectious Diseases, Istituto Superiore Di Sanità, Rome, Italy.
Flavia RiccardoDepartment of Infectious Diseases, Istituto Superiore Di Sanità, Rome, Italy.
Patrizio Pezzotti *Department of Infectious Diseases, Istituto Superiore Di Sanità, Rome, Italy.
Piero Poletti *Center for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Stefano Merler *Center for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy. merler@fbk.eu.

Funding

European Commission 874850European Commission PE00000007, INF-ACT
6 · The paper itself

Abstract

Quantifying the potential spatial spread of an infectious pathogen is key to defining effective containment and control strategies. The aim of this study is to estimate the risk of SARS-CoV-2 transmission at different distances in Italy before the first regional lockdown was imposed, identifying important sources of national spreading. To do this, we leverage on a probabilistic model applied to daily symptomatic cases retrospectively ascertained in each Italian municipality with symptom onset between January 28 and March 7, 2020. Results are validated using a multi-patch dynamic transmission model reproducing the spatiotemporal distribution of identified cases. Our results show that the contribution of short-distance (

Indexed as

COVID-19SARS-CoV-2HumansItalyModels, StatisticalPandemicsRetrospective StudiesSpatio-Temporal AnalysisCOVID-19Infection spreadSARS-CoV-2Spatial diffusionSpatial modelTransmission distance

Identifiers

PMID38684947
PMCPMC11057115

What OpenQuestion holds

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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.