Evidence map›Paper›PMID 39651472›Full record

SynthesisFrontiers in public health2024

Innovating health prevention models in detecting infectious disease outbreaks through social media data: an umbrella review of the evidence.

Monica Giancotti, Milena Lopreite, Marianna Mauro, Michelangelo Puliga

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in public health, 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

4 authors.

Monica GiancottiDepartment of Law, Economics and Social Sciences, Magna Graecia University, Catanzaro, Italy.
Milena LopreiteDepartment of Economics, Statistics and Finance, University of Calabria, Cosenza, Italy.
Marianna MauroDepartment of Clinical and Experimental Medicine, Magna Graecia University, Catanzaro, Italy.
Michelangelo PuligaScuola Superiore Sant'Anna, Institute of Management, Pisa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction and objective: The number of literature reviews examining the use of social media in detecting emerging infectious diseases has recently experienced an unprecedented growth. Yet, a higher-level integration of the evidence is still lacking. This study aimed to synthesize existing systematic literature reviews published on this topic, offering an overview that can help policymakers and public health authorities to select appropriate policies and guidelines. Methods: We conducted an umbrella review: a review of systematic reviews published between 2011 and 2023 following the PRISMA statement guidelines. The review protocol was registered in the PROSPERO database (CRD42021254568). As part of the search strategy, three database searches were conducted, specifically in PubMed, Web of Science, and Google Scholar. The quality of the included reviews was determined using A Measurement Tool to Assess Systematic Reviews 2. Results: Synthesis included 32 systematic reviews and 3,704 primary studies that investigated how the social media listening could improve the healthcare system's efficiency in terms of a timely response to treat epidemic situations. Most of the included systematic reviews concluded showing positive outcomes when using social media data for infectious disease surveillance. Conclusion: Systematic reviews showed the important role of social media in predicting and detecting disease outbreaks, potentially reducing morbidity and mortality through swift public health action. The policy interventions strongly benefit from the continued use of online data in public health surveillance systems because they can help in recognizing important patterns for disease surveillance and significantly improve the disease prediction abilities of the traditional surveillance systems. Systematic Review Registration: http://www.crd.york.ac.uk/PROSPERO, identifier [CRD42021254568].

Indexed as

Disease OutbreaksSocial MediaHumansPublic HealthSystematic Reviews as Topicemerging infectious diseaseshealth policysocial mediasurveillanceumbrella review

Identifiers

PMID39651472
PMCPMC11621043

What OpenQuestion holds

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LicenceCC BY
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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.