Modelling the dynamics of an experimental host-pathogen microcosm within a hierarchical Bayesian framework.

ABSTRACT: The advantages of Bayesian statistical approaches, such as flexibility and the ability to acknowledge uncertainty in all parameters, have made them the prevailing method for analysing the spread of infectious diseases in human or animal populations. We introduce a Bayesian approach to experimental host-pathogen systems that shares these attractive features. Since uncertainty in all parameters is acknowledged, existing information can be accounted for through prior distributions, rather than through fixing some parameter values. The non-linear dynamics, multi-factorial design, multiple measurements of responses over time and sampling error that are typical features of experimental host-pathogen systems can also be naturally incorporated. We analyse the dynamics of the free-living protozoan

SUBMITTER: Lunn D 

PROVIDER: S-EPMC3732293 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature