Subject Modeling-Based Analysis of the Evolution and Intervention Strategies of Major Emerging Infectious Disease Events
Haixiang Guo,1,2 Tiantian Zhao,1 Yuzhe Zou,1 Beijia Zhang,1 Yuyan Cheng1 1School of Economics and Management, China University of Geosciences, Wuhan, People’s Republic of China; 2The Laboratory of Natural Disaster Risk Prevention and Emergency Management, China University of Geosciences, Wuhan, Peop...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Dove Medical Press
2025-04-01
|
| Series: | Risk Management and Healthcare Policy |
| Subjects: | |
| Online Access: | https://www.dovepress.com/subject-modeling-based-analysis-of-the-evolution-and-intervention-stra-peer-reviewed-fulltext-article-RMHP |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Haixiang Guo,1,2 Tiantian Zhao,1 Yuzhe Zou,1 Beijia Zhang,1 Yuyan Cheng1 1School of Economics and Management, China University of Geosciences, Wuhan, People’s Republic of China; 2The Laboratory of Natural Disaster Risk Prevention and Emergency Management, China University of Geosciences, Wuhan, People’s Republic of ChinaCorrespondence: Haixiang Guo, Email faterdumk0732@sina.comObjective: Due to the popularity of the Internet and the extensive use of new media, after the occurrence of infectious diseases, the spread of social media information greatly affects the group’s opinion and cognition and even the health behaviors they take, thus affecting the spread of infectious diseases. Therefore, this paper studies the event evolution from multiple dimensions.Methods: To address this gap, we developed a three-layer model framework of major infectious disease event evolution based on subject modeling. This framework integrates three key factors—health transmission, perspective interaction, and risk perception—to analyze group perspective evolution, behavioral change, and virus transmission processes. The model’s effectiveness was evaluated through simulation and sensitivity analysis. In addition, we conducted an empirical analysis by constructing a social media health transmission effect index system to identify the critical factors affecting health transmission.Results: Simulation results reveal that among the three factors, health transmission has the most significant impact on the evolution of group perspectives during infectious disease events. Moreover, the dynamics of public viewpoint evolution influence individual decisions regarding the adoption of non-pharmacological interventions, which are shown to effectively reduce both the transmission rate of the virus and the peak number of infections.Conclusion: The findings of this study enhance our understanding of the complex mechanisms and evolutionary pathways in infectious disease events. By integrating multiple dimensions of event evolution, the proposed model offers valuable insights for the design of effective countermeasures and strategies in emergency management and response to infectious disease outbreaks.Keywords: infectious disease events, viewpoint evolution, behavior change, subject modeling, simulation |
|---|---|
| ISSN: | 1179-1594 |