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

Autor: Nigel P. French, Philip E. Carter, Jonathan C. Marshall, David T. S. Hayman, Jackie Benschop, Patrick J. Biggs, Samuel J. Bloomfield, Timothy G. Vaughan
Jazyk: angličtina
Rok vydání: 2019
Předmět:
0301 basic medicine
Bacterial Diseases
Salmonellosis
Epidemiology
Pathology and Laboratory Medicine
Geographical locations
law.invention
Coalescent theory
Disease Outbreaks
0302 clinical medicine
Effective population size
law
Salmonella
Statistics
Medicine and Health Sciences
Data Management
education.field_of_study
Multidisciplinary
Simulation and Modeling
Sampling (statistics)
Phylogenetic Analysis
Bacterial Pathogens
Phylogenetics
Transmission (mechanics)
Infectious Diseases
Medical Microbiology
Medicine
Pathogens
Research Article
Computer and Information Sciences
Population Size
Science
Population
Bayesian probability
Oceania
Biology
Research and Analysis Methods
Microbiology
Models
Biological
03 medical and health sciences
Population Metrics
Enterobacteriaceae
Effective Population Size
Genetics
Animals
Evolutionary Systematics
Animal Models of Disease
education
Microbial Pathogens
Taxonomy
Evolutionary Biology
Salmonella Infections
Animal
Population Biology
Bacteria
Host (biology)
Organisms
Outbreak
Biology and Life Sciences
Bayes Theorem
Animal Models of Infection
030104 developmental biology
Animal Studies
People and places
030217 neurology & neurosurgery
Population Genetics
New Zealand
Zdroj: PLoS ONE
PLoS ONE, 14 (7)
PLoS ONE, Vol 14, Iss 7, p e0214169 (2019)
ISSN: 1932-6203
Popis: 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 transmissions between the host populations or the amount of time spent in each host population. The DTA model was inaccurate because it assumed the number of isolates sampled from each host population was proportional to the number of individuals infected within each host population. The SC model was inaccurate possibly because it assumed that each host population's effective population size was constant over the course of the simulated outbreaks. This study highlights the need for phylodynamic models that can take into consideration factors that influence the characteristics and behavior of outbreaks, e.g. changing effective population sizes, variation in infectious periods, intra-population transmissions, and disproportionate sampling of infected individuals.
PLoS ONE, 14 (7)
ISSN:1932-6203
Databáze: OpenAIRE
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