Stochastic epidemics in a heterogeneous community (Part III of the book Stochastic Epidemic Models and Inference)

Abstract

This document is the Part III of the book 'Stochastic Epidemic Models with Inference' edited by Tom Britton and Etienne Pardoux. Plan of the chapter: 1) Random Graphs, 2) The Reproduction Number R0, 3) SIR Epidemics on Configuration Model Graphs, 4) Statistical Description of Epidemics Spreading on Networks: The Case of Cuban HIV.

Lecture notes of a course given in a CIMPA school in Ziguinchor (Dec. 2015)

References in corpus (8)

• Resolution limit in community detection
• Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems
• A microscopic probabilistic description of a locally regulated population and macroscopic approximations
• Modularity clustering is force-directed layout
• Statistical inference for epidemic processes in a homogeneous community (Part IV of the book Stochastic Epidemic Models and Inference)
• Stochastic epidemics in a heterogeneous community (Part III of the book Stochastic Epidemic Models and Inference)
• Partitioning and modularity of graphs with arbitrary degree distribution
• Introduction to statistical inference for infectious diseases

Cited by in corpus (8)

• Statistical inference for epidemic processes in a homogeneous community (Part IV of the book Stochastic Epidemic Models and Inference)
• Stochastic epidemics in a heterogeneous community (Part III of the book Stochastic Epidemic Models and Inference)
• A probabilistic framework for particle-based reaction-diffusion dynamics using classical Fock space representations
• Incentives, lockdown, and testing: from Thucydides's analysis to the COVID-19 pandemic
• Stochastic approach to epidemic spreading
• Latent event history models for quasi-reaction systems
• Dynamics of systems with varying number of particles: from Liouville equations to general master equations for open systems
• A SIR epidemic model on a refining spatial grid II-Central limit theorem