Investigation of the validity of two Bayesian ancestral state reconstruction models for estimating Salmonella transmission during outbreaks.

ABSTRACT: Ancestral state reconstruction models use genetic data to characterize a group of organisms' common ancestor. These models have been applied to salmonellosis outbreaks to estimate the number of transmissions between different animal species that share similar geographical locations, with animal host as the state. However, as far as we are aware, no studies have validated these models for outbreak analysis. In this study, salmonellosis outbreaks were simulated using a stochastic Susceptible-Infected-Recovered model, and the host population and transmission parameters of these simulated outbreaks were estimated using Bayesian ancestral state reconstruction models (discrete trait analysis (DTA) and structured coalescent (SC)). These models were unable to accurately estimate the number of tran

SUBMITTER: Bloomfield S 

PROVIDER: S-EPMC6645465 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature