Evidence map›Paper›PMID 41751745›Full record

ArticleEntropy (Basel, Switzerland)2026

Coupled Dynamics of Vaccination Behavior and Epidemic Spreading on Multilayer Higher-Order Networks.

Zhishuang Wang, Guoqiang Zeng, Qian Yin, Linyuan Guo, Zhiyong Hong

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Zhishuang WangSchool of Electronics and Information Engineering, Wuyi University, Jiangmen 529020, China.
Guoqiang ZengSchool of Electronics and Information Engineering, Wuyi University, Jiangmen 529020, China.ORCID 0009-0001-9722-6561
Qian YinSchool of Electronics and Information Engineering, Wuyi University, Jiangmen 529020, China.
Linyuan GuoSchool of Electronics and Information Engineering, Wuyi University, Jiangmen 529020, China.
Zhiyong HongSchool of Electronics and Information Engineering, Wuyi University, Jiangmen 529020, China.ORCID 0000-0002-5409-2962

Funding

Guangdong Basic and Applied Basic Research Foundation 2023A1515110305Guangdong Provincial Department of Education Youth Innovative Talents Project 2023KQNCX087Jiangmen Basic and Theoretical Science Research Technology Program Project 2023JC01008National Natural Science Foundation of China 62503372
6 · The paper itself

Abstract

Vaccination behavior and epidemic spreading are strongly intertwined processes, and their coevolution is often shaped by both individual decision-making and social interactions. However, most existing studies model such interactions at the pairwise level, overlooking the potential impact of higher-order social influence arising from group interactions. In this work, we develop a coupled vaccination-epidemic spreading model on multilayer higher-order networks, where vaccination behavior evolves on a simplicial complex and epidemic propagation occurs on a physical contact network. The model incorporates imperfect vaccine efficacy, allowing vaccinated individuals to become infected, and introduces a hybrid vaccination strategy that combines rational cost-benefit evaluation with social influence from both pairwise and higher-order interactions, as well as negative effects induced by vaccine failure. By constructing the coupled dynamical equations, we analytically derive the epidemic outbreak threshold and elucidate how higher-order interactions, behavioral responses, and vaccine-related parameters jointly affect epidemic dynamics. Numerical simulations on networks with different structural properties validate the theoretical results and reveal pronounced structure-dependent effects. The results show that higher-order social interactions can significantly reshape vaccination behavior and epidemic prevalence, while network heterogeneity and vaccine imperfection play crucial roles in determining the outbreak threshold and steady-state infection level. These results emphasize the necessity of incorporating higher-order interactions together with realistic vaccination behavior into epidemic modeling and offer new insights for the design of effective vaccination strategies.

Indexed as

coevolutionary dynamicsepidemic spreadinghigher-order networksvaccination behavior

Identifiers

PMID41751745
PMCPMC12939874

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.