Infectious Disease Dynamics Inferred from Genetic Data via Sequential Monte Carlo.

ABSTRACT: Genetic sequences from pathogens can provide information about infectious disease dynamics that may supplement or replace information from other epidemiological observations. Most currently available methods first estimate phylogenetic trees from sequence data, then estimate a transmission model conditional on these phylogenies. Outside limited classes of models, existing methods are unable to enforce logical consistency between the model of transmission and that underlying the phylogenetic reconstruction. Such conflicts in assumptions can lead to bias in the resulting inferences. Here, we develop a general, statistically efficient, plug-and-play method to jointly estimate both disease transmission and phylogeny using genetic data and, if desired, other epidemiological observations. This m

SUBMITTER: Smith RA 

PROVIDER: S-EPMC5815633 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature