Contagion Source Detection in Epidemic and Infodemic Outbreaks: Mathematical Analysis and Network Algorithms

Abstract

This monograph provides an overview of the mathematical theories and computational algorithm design for contagion source detection in large networks. By leveraging network centrality as a tool for statistical inference, we can accurately identify the source of contagions, trace their spread, and predict future trajectories. This approach provides fundamental insights into surveillance capability and asymptotic behavior of contagion spreading in networks. Mathematical theory and computational algorithms are vital to understanding contagion dynamics, improving surveillance capabilities, and developing effective strategies to prevent the spread of infectious diseases and misinformation.

arXiv commentSuggested Citation: Chee Wei Tan and Pei-Duo Yu (2023), "Contagion Source Detection in Epidemic and Infodemic Outbreaks: Mathematical Analysis and Network Algorithms", Foundations and Trends in Networking: Vol. 13: No. 2-3, pp 107-251. http://dx.doi.org/10.1561/1300000068

References in corpus (20)

• The science of fake news
• The spread of epidemic disease on networks
• Immunization of complex networks
• The physics of spreading processes in multilayer networks
• Inferring the origin of an epidemic with a dynamic message-passing algorithm
• The Anatomy of a Scientific Rumor
• Optimal Resource Allocation for Network Protection Against Spreading Processes
• Identifying Infection Sources and Regions in Large Networks
• Rooting out the Rumor Culprit from Suspects
• How to Identify an Infection Source with Limited Observations
• Centrality measures and thermodynamic formalism for complex networks
• Automatic Detection of Influential Actors in Disinformation Networks
• Infection Spreading and Source Identification: A Hide and Seek Game
• Epidemic Source Detection in Contact Tracing Networks: Epidemic Centrality in Graphs and Message-Passing Algorithms
• Physical Zero-Knowledge Proof for Ripple Effect
• Coronavirus Contact Tracing: Evaluating The Potential Of Using Bluetooth Received Signal Strength For Proximity Detection
• Bayesian Discovery of Threat Networks
• Network Detection Theory and Performance
• On the Properties of Gromov Matrices and their Applications in Network Inference
• Network infection source identification under the SIRI model