Approximating individual risk of infection in a Markov chain epidemic network model with a deterministic system

DOI10.1080/10236198.2016.1201476zbMath1375.37180OpenAlexW2462452103MaRDI QIDQ2964221

Miaohua Jiang

Publication date: 23 February 2017

Published in: Journal of Difference Equations and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10236198.2016.1201476

zbMATH Keywords

epidemicsinfectious diseasenetwork modelindividual risk

Mathematics Subject Classification ID

Epidemiology (92D30) Dynamical systems in biology (37N25) Population dynamics (general) (92D25) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10)

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Cites Work

• Unnamed Item
• Finding the probability of infection in an SIR network is NP-hard
• Contact network epidemiology: Bond percolation applied to infectious disease prediction and control
• Dynamical networks: interplay of topology, interactions and local dynamics
• Interplay of node connectivity and epidemic rates in the dynamics of epidemic networks
• Effects of network topology, transmission delays, and refractoriness on the response of coupled excitable systems to a stochastic stimulus
• Networks

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