Modeling, Dynamics, and Control of Infectious Diseases via Complex Network Approaches

Dear Colleagues,

We are pleased to invite you to contribute to a Topic on "Modeling, Dynamics, and Control of Infectious Diseases via Complex Network Approaches". Infectious diseases continue to pose significant threats to global public health, as evidenced by recurrent pandemics, emerging pathogens, and strains resistant to drugs and vaccines. The spread of infectious agents is inherently shaped by virus properties and the underlying physical proximity, contact structures, and mobility patterns among hosts—all of which can be naturally represented as complex networks. In recent years, the fusion of network science, dynamical systems theory, and data-driven epidemiology has yielded profound insights into virus transmission, disease spread, outbreak prediction, and optimal intervention strategies. This Topic aims to showcase cutting-edge research that leverages complex network methodologies to address fundamental and applied questions in infectious disease epidemiology. This Topic includes, but is not limited to, the following topics:

• Network reconstruction and inference from epidemiological data;
• Epidemic spreading models on static, temporal, and adaptive networks;
• Stability analysis of disease-free and endemic equilibria in network-coupled systems;
• Optimal control and vaccination strategies on heterogeneous networks;
• Robust and adaptive control for epidemic suppression under uncertainty;
• Intermittent, pulse, and event-triggered intervention policies;
• Multi-layer and multiplex network models for co-infections and coupled diseases;
• Delayed dynamics and stochastic effects in network epidemic models;
• Fractional-order epidemic models and their numerical simulations on complex topologies;
• Data-driven forecasting, early warning signals, and real-time monitoring using network metrics;
• Network-based economic and behavioral epidemiology, including public health decision-making.

We invite researchers to submit their original research papers, comprehensive review articles, and forward-looking perspectives that advance the understanding of infectious disease dynamics through the lens of complex networks. The objective of this Topic is to foster interdisciplinary dialog among mathematicians, physicists, computer scientists, epidemiologists, and public health experts, and to accelerate the translation of network-based theories into practical tools for disease prevention and control.

We look forward to receiving your valuable contributions.

Prof. Dr. Wei Yao
Prof. Dr. Hongying Shu
Topic Editors