Coupling Individual Psychological Security and Information for Modeling the Spread of Infectious Diseases

Background: Faced with the profound impact of major infectious diseases on public life and economic development, humans have long sought to understand disease transmission and intervention strategies. To better explore the impact of individuals’ different coping behaviors—triggered by changes in their psychological security due to public information and external environmental changes—on the spread to infectious diseases, the model will place greater emphasis on quantifying psychological factors to make it more aligned with real-world situations. Methods: To better understand the interplay between information dissemination and disease transmission, we propose a two-layer network model that incorporates psychological safety factors. Results: Our model reveals key insights into disease transmission dynamics: (1) active defense behaviors help reduce both disease spread and information diffusion; (2) passive resistance behaviors expand disease transmission and may trigger recurrence but enhance information spread; (3) high-timeliness, low-fuzziness information reduces the peak of the initial infection but does not significantly curb overall disease spread, and the rapid dissemination of disease-related information is most effective in limiting the early stages of transmission; and (4) community structures in information networks can effectively curb the spread of infectious diseases. Conclusions: These findings offer valuable theoretical support for public health strategies and disease prevention after government information release.

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Publication Details

Journal
Systems
Published
2025-08-01
DOI
https://doi.org/10.3390/systems13080637
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Coupling Individual Psychological Security and Information for Modeling the Spread of Infectious Diseases

X. Sean Wang, Jianlin Zhou, Na Li, Haiyan Liu
Systems
COVID-19 epidemiological studies
article

Coupling Individual Psychological Security and Information for Modeling the Spread of Infectious Diseases

X. Sean Wang, Jianlin Zhou, Na Li, Haiyan Liu
article en

Abstract

Background: Faced with the profound impact of major infectious diseases on public life and economic development, humans have long sought to understand disease transmission and intervention strategies. To better explore the impact of individuals’ different coping behaviors—triggered by changes in their psychological security due to public information and external environmental changes—on the spread to infectious diseases, the model will place greater emphasis on quantifying psychological factors to make it more aligned with real-world situations. Methods: To better understand the interplay between information dissemination and disease transmission, we propose a two-layer network model that incorporates psychological safety factors. Results: Our model reveals key insights into disease transmission dynamics: (1) active defense behaviors help reduce both disease spread and information diffusion; (2) passive resistance behaviors expand disease transmission and may trigger recurrence but enhance information spread; (3) high-timeliness, low-fuzziness information reduces the peak of the initial infection but does not significantly curb overall disease spread, and the rapid dissemination of disease-related information is most effective in limiting the early stages of transmission; and (4) community structures in information networks can effectively curb the spread of infectious diseases. Conclusions: These findings offer valuable theoretical support for public health strategies and disease prevention after government information release.

SystemsVol. 13(8)
Beijing Normal University (CN), China University of Geosciences (Beijing) (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 77%
COVID-19 epidemiological studies
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Coupling Individual Psychological Security and Information for Modeling the Spread of Infectious Diseases — X. Sean Wang, Jianlin Zhou, et al. · Systems (2025) | TGRS Research Map | TGRS