Using approximate Bayesian computation to estimate transmission rates of nosocomial pathogens
Drovandi, Christopher C. & Pettitt, Anthony N. (2011) Using approximate Bayesian computation to estimate transmission rates of nosocomial pathogens. Statistical Communications in Infectious Diseases, 3(1).
In this paper, we apply a simulation based approach for estimating transmission rates of nosocomial pathogens. In particular, the objective is to infer the transmission rate between colonised health-care practitioners and uncolonised patients (and vice versa) solely from routinely collected incidence data. The method, using approximate Bayesian computation, is substantially less computer intensive and easier to implement than likelihood-based approaches we refer to here. We find through replacing the likelihood with a comparison of an efficient summary statistic between observed and simulated data that little is lost in the precision of estimated transmission rates. Furthermore, we investigate the impact of incorporating uncertainty in previously fixed parameters on the precision of the estimated transmission rates.
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|Item Type:||Journal Article|
|Keywords:||approximate Bayesian computation, likelihood-free inference, Methicillin-resistant Staphylococcus aureus, Markov process, nosocomial pathogen, sequential Monte Carlo|
|Subjects:||Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400)|
|Divisions:||Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2012 Walter de Gruyter GmbH & Co. KG|
|Copyright Statement:||The final publication is available at www.degruyter.com|
|Deposited On:||14 May 2012 22:48|
|Last Modified:||31 Jul 2013 21:58|
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