Modelling and inference for epidemic models featuring non-linear infection pressure

DOI10.1016/j.mbs.2012.03.007zbMath1250.92039OpenAlexW1968293561WikidataQ44096423 ScholiaQ44096423MaRDI QIDQ449499

J. Herrera, D. Rodríguez-Gómez

Publication date: 30 August 2012

Published in: Mathematical Biosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.mbs.2012.03.007

zbMATH Keywords

Bayesian inferenceMarkov chain Monte Carlo methodsSIR model

Mathematics Subject Classification ID

Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (5)

Direct likelihood-based inference for discretely observed stochastic compartmental models of infectious disease ⋮ Posterior predictive checking for partially observed stochastic epidemic models ⋮ Final outcome probabilities for SIR epidemic model ⋮ Bayes factors for partially observed stochastic epidemic models ⋮ An epidemic model with short-lived mixing groups

Cites Work

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• Time Series Modelling of Childhood Diseases: A Dynamical Systems Approach
• Population Dynamics and the Epidemiological Model Proposed by Severo
• Semiparametric Estimation of the Duration of Immunity from Infectious Disease Time Series: Influenza as a Case-Study

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