Evidence map›Paper›PMID 40427785›Full record

ArticleInternational journal of environmental research and public health2025

Mapping Infodemic Responses: A Geospatial Analysis of COVID-19 Discourse on Twitter in Italy.

Gabriela Fernandez, Siddharth Suresh-Babu, Domenico Vito

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2025. 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

3 authors.

Gabriela FernandezMetabolism of Cities Living Laboratory, Center for Human Dynamics in the Mobile Age, Department of Geography, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182, USA.ORCID 0000-0002-7271-0250
Siddharth Suresh-BabuMetabolism of Cities Living Laboratory, Center for Human Dynamics in the Mobile Age, Department of Geography, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182, USA.ORCID 0009-0004-6878-1138
Domenico VitoMetabolism of Cities Living Laboratory, Center for Human Dynamics in the Mobile Age, Department of Geography, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182, USA.ORCID 0000-0001-7659-9361

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic intensified concerns about misinformation, sparking interest in the field of infodemiology, which examines the spread and impact of information on public health perceptions. This research examines how geographic location influenced COVID-19 discourse across 10 Italian cities by analyzing geographically tagged Twitter data. Our network analysis of 4792 high-degree nodes identifies key information spreaders and community structures, while spatiotemporal mapping reveals regional variations in information patterns and influential narratives. Results demonstrate significant geographic and cultural influences on public discourse. In Milan and Rome, economic and political narratives dominated, suggesting targeted messaging about economic recovery and government transparency. Southern regions like Naples require trust-building through community-led initiatives addressing cultural health beliefs. The study identified a clear dichotomy among influencers: established public figures provided evidence-based information, while another group cultivated followings through conspiracy theories, creating echo chambers for skeptical views. This research informs strategies for location-specific information campaigns, helping public health agencies combat misinformation more effectively. Findings emphasize the need for context-specific interventions that consider geographic, cultural, and socioeconomic factors to enhance community resilience during health emergencies.

Indexed as

CommunicationCOVID-19Information DisseminationSocial MediaHumansItalyPandemicsPublic HealthSARS-CoV-2COVID-19 misinformationgeospatial analysisinfodemiologyItalypublic perceptionsocial media analysisTwitter

Identifiers

PMID40427785
PMCPMC12110805

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.