Analysis and Control of Epidemics: A survey of spreading processes on complex networks
arXiv:1505.00768
Abstract
This article reviews and presents various solved and open problems in the development, analysis, and control of epidemic models. We are interested in presenting a relatively concise report for new engineers looking to enter the field of spreading processes on complex networks.
References in corpus (8)
- Epidemic processes in complex networks
- Threshold effects for two pathogens spreading on a network
- Towards a characterization of behavior-disease models
- Analysis of complex contagions in random multiplex networks
- Optimal Vaccine Allocation to Control Epidemic Outbreaks in Arbitrary Networks
- Distributed Resource Allocation for Epidemic control
- Exponential extinction time of the contact process on finite graphs
- Data-Driven Allocation of Vaccines for Controlling Epidemic Outbreaks
Cited by in corpus (16)
- Optimal Containment of Epidemics in Temporal and Adaptive Networks
- Forecasting Time Series with VARMA Recursions on Graphs
- Leveraging local h-index to identify and rank influential spreaders in networks
- Data-Driven Methods for Present and Future Pandemics: Monitoring, Modelling and Managing
- Interacting spreading processes in multilayer networks
- Cyber-Social Systems: Modeling, Inference, and Optimal Design
- A mean-field analysis of a network behavioural-epidemic model
- Optimal adaptive testing for epidemic control: combining molecular and serology tests
- Bifurcation analysis of the Microscopic Markov Chain Approach to contact-based epidemic spreading in networks
- Analysis of Exact and Approximated Epidemic Models over Complex Networks
- Sensor Selection Cost Optimization for Tracking Structurally Cyclic Systems: a P-Order Solution
- GAEA: Graph Augmentation for Equitable Access via Reinforcement Learning
- Mitigating Biological Epidemic on Heterogeneous Social Networks
- Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs (Extended Version)
- Transfer Learning for Node Regression Applied to Spreading Prediction
- A hospital demand and capacity intervention approach for COVID-19 in the UK