HIV with contact tracing: a case study in approximate Bayesian computation

• Published in: Biostatistics (Oxford, England) Vol. 11; no. 4; pp. 644 - 660
• Main Authors: Blum, Michael G B, Tran, Viet Chi
• Format: Journal Article
• Language: English
• Published: England Oxford Publishing Limited (England) 01.10.2010; Oxford University Press (OUP)
• Subjects: Acquired immune deficiency syndrome; AIDS; Algorithms; Applications; Bayes Theorem; Bayesian analysis; Biostatistics; Computation; Computer Simulation; Contact Tracing; Cuba - epidemiology; Epidemiology; HIV; HIV Infections - epidemiology; HIV Infections - transmission; Human immunodeficiency virus; Humans; Life Sciences; Linear Models; Markov Chains; Models, Biological; Monte Carlo Method; Monte Carlo simulation; Nonlinear Dynamics; Santé publique et épidémiologie; Statistics; Stochastic Processes; Cuba; Mathematical epidemiology; likelihood-free inference; stochastic SIR model; simulation-based inference; unobserved infectious population

Missing data is a recurrent issue in epidemiology where the infection process may be partially observed. Approximate Bayesian computation (ABC), an alternative to data imputation methods such as Markov chain Monte Carlo (MCMC) integration, is proposed for making inference in epidemiological models....