Recently, the research team led by Professor Wang Wei from the College of Public Health, Chongqing Medical University published a research paper titled “Modelling two competing infectious diseases in a metropolitan contact network” in the authoritative international journal “Chaos, Solitons and Fractals”.
The research team constructed age-stratified contact networks covering individuals aged 0 to 85 based on census data from global metropolises and used dimensionality reduction methods to simplify the high-dimensional dynamical system into a single equation. Through numerical simulations of transmission scenarios in major cities like New York, the accuracy of this approach was validated, revealing three key transmission modes inherent in the system. Additionally, the study quantitatively assessed the impact of different environments on transmission dynamics, showing that workplaces significantly facilitate the spread of highly transmissible diseases.
Phase diagram of the endemic states for competitive epidemic spreading
The research findings not only deepen the understanding of urban infectious disease transmission dynamics but also provide methodological support for interdisciplinary research. For example, in public health, the models can be used to evaluate the effectiveness of vaccination strategies or non-pharmaceutical interventions; in urban planning, they can optimise the layout design of densely populated contact areas to reduce transmission risks. The research team stated that future work will further explore multi-pathogen co-transmission mechanisms and dynamic intervention strategies to promote the translation of research outcomes into practical applications.
Journal Introduction:
“Chaos, Solitons and Fractals” was founded in 1991 and is a significant international journal in the field of nonlinear science, focusing on interdisciplinary research in chaos theory, soliton dynamics, and fractal structures. The journal is classified as Tier 1 (Top) by the Chinese Academy of Sciences and the China Institute of Scientific and Technical Information. It holds considerable academic influence in the fields of nonlinear science and complex systems. The journal is dedicated to publishing high-quality research combining theoretical innovation with empirical applications, covering cutting-edge topics such as infectious disease dynamics modelling and urban complex network analysis, aiming to promote interdisciplinary translational applications of complex systems theory.
Full Article Link:
https://doi.org/10.1016/j.chaos.2025.116282
(Translated by AI)
