Estimation of temporal covariances in pathogen dynamics using Bayesian multivariate autoregressive models.

ABSTRACT: It is well recognised that animal and plant pathogens form complex ecological communities of interacting organisms within their hosts, and there is growing interest in the health implications of such pathogen interactions. Although community ecology approaches have been used to identify pathogen interactions at the within-host scale, methodologies enabling robust identification of interactions from population-scale data such as that available from health authorities are lacking. To address this gap, we developed a statistical framework that jointly identifies interactions between multiple viruses from contemporaneous non-stationary infection time series. Our conceptual approach is derived from a Bayesian multivariate disease mapping framework. Importantly, our approach captures within- and

SUBMITTER: Mair C 

PROVIDER: S-EPMC6934324 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature