Evidence map›Paper›PMID 42774158›Full record

ArticleFrontiers in public health2026

Public information sharing during public health emergencies: an adaptive-network evolutionary game.

Yiling Ma, Wei Feng

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. 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

2 authors.

Yiling MaSchool of Economics and Trade, Hunan University, Changsha, China.
Wei FengSchool of Public Administration and Tourism, Hunan University of Technology and Business, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Public health emergencies can generate verified sharing, opportunistic dissemination, and strategic silence within the same communication environment, yet diffusion-centered approaches offer limited explanation of how these contrasting behaviors emerge together or change as communication relationships evolve. Methods: This study develops an adaptive-network evolutionary game in which individuals choose among verified/corrective sharing, opportunistic sharing, and silence. The model links information value, verification burden, attention incentives, targeted sanctions, and participation-related liability to local interaction and adaptive rewiring. Results: Valuable and low-burden credible information favors verified sharing, whereas strong attention incentives favor opportunistic dissemination. Targeted accountability can redirect behavior toward credible participation, while generalized liability weakens good-faith sharing and, when combined with broader withdrawal incentives, can contribute to information vacuums. Discussion: By separating information quality, information absence, and structural connectivity, the study shifts attention from diffusion volume to the joint evolution of behavior and communication relationships. The findings provide a mechanism-based basis for designing public-health communication policies that constrain harmful dissemination without discouraging credible participation.

Indexed as

EmergenciesGame TheoryInformation DisseminationPublic HealthCommunicationHumansadaptive networkevolutionary gamehealth misinformationinfodemic managementinformation sharingpublic health emergenciesrisk communication

Identifiers

PMID42774158
PMCPMC13593605

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.