Manuscript Topics
The importance of network-oriented approaches toward understanding and controlling disease spread in human social networks is widely accepted. Although there exists a rich literature on the modeling, analysis, and control of epidemic spreading processes on complex networks, the current COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has highlighted our need for increased research efforts to properly prepare us for the future spread of unknown diseases. For example, due to the lack of reliable networked models, authorities' interventions to the current pandemic are often designed without a detailed understanding of how effective the interventions will be. Therefore, to fill in this gap between theory and practice, further interdisciplinary research efforts are expected to deepen our theoretical understanding of the modeling, analysis, and control of networked epidemics processes.

In this context, we invite researchers to contribute original research articles that fall within the broad category of modeling, analysis, and control of networked epidemic spreading processes (not necessarily limited to biological epidemic processes). Topics include, but are not limited to, the following:
- Networked spreading models
- Parameter estimation
- Networked surveillance systems
- Stability analysis of epidemic models
- Epidemic thresholds
- Reproduction numbers
- Optimal control
- Resource allocation for containment
- Non-pharmaceutical interventions
- Temporal networks
- Interventions and human behaviors
- Interventions and economy
- Preparation for future pandemics
- Data-driven methods
- Machine learning approaches

We specifically welcome contributions using theoretical approaches to address the topics mentioned above in the context of networks. A variety of mathematical approaches and frameworks are welcome, provided that they provide a deeper understanding of the modeling, analysis, and control of networked epidemic processes. Papers in which theoretical analyses are supported by numerical simulations are encouraged.

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