Opinion-driven regulation of multi-strain pathogen transmission across species

This study investigates the fundamental mechanisms underlying cross-species, multi-strain transmission in ecosystems from the opinion of group opinion dynamics. A multilayer interaction framework is proposed, incorporating signed-weighted social network dynamics to quantify group-level opinions and dynamically adjust key epidemiological parameters in real time. The analysis reveals that (1) infection pressure alters group opinion thresholds via cognitive-behavioral feedback, while the emerging collective consensus reciprocally regulates transmission intensity, forming a closed-loop feedback mechanism. (2) The topology of the opinion network governs epidemic phase transitions, inducing a bistable regime characterized by either low-risk (opinion cohesion) or high-risk (opinion polarization) states. By identifying critical nodes within the signed social graph, the study transforms group opinion intensity into dynamic warning thresholds, enabling targeted ecological interventions.

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Publication Details

Journal
Chaos An Interdisciplinary Journal of Nonlinear Science
Published
2026-02-01
DOI
https://doi.org/10.1063/5.0302437
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
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article

Opinion-driven regulation of multi-strain pathogen transmission across species

Hongchun Qu, Shidong Zhai, Jiyu Zhang, Jun Ma
Chaos An Interdisciplinary Journal of Nonlinear Science
Opinion Dynamics and Social Influence
article

Opinion-driven regulation of multi-strain pathogen transmission across species

Hongchun Qu, Shidong Zhai, Jiyu Zhang, Jun Ma
article en

Abstract

This study investigates the fundamental mechanisms underlying cross-species, multi-strain transmission in ecosystems from the opinion of group opinion dynamics. A multilayer interaction framework is proposed, incorporating signed-weighted social network dynamics to quantify group-level opinions and dynamically adjust key epidemiological parameters in real time. The analysis reveals that (1) infection pressure alters group opinion thresholds via cognitive-behavioral feedback, while the emerging collective consensus reciprocally regulates transmission intensity, forming a closed-loop feedback mechanism. (2) The topology of the opinion network governs epidemic phase transitions, inducing a bistable regime characterized by either low-risk (opinion cohesion) or high-risk (opinion polarization) states. By identifying critical nodes within the signed social graph, the study transforms group opinion intensity into dynamic warning thresholds, enabling targeted ecological interventions.

Chaos An Interdisciplinary Journal of Nonlinear ScienceVol. 36(2)
Chongqing University of Posts and Telecommunications (CN), Lanzhou University of Technology (CN)
Openalex Percentile: Top 67%
Opinion Dynamics and Social Influence
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