Bayesian reconstruction of transmission trees from genetic sequences and uncertain infection times.

ABSTRACT: Genetic sequence data of pathogens are increasingly used to investigate transmission dynamics in both endemic diseases and disease outbreaks. Such research can aid in the development of appropriate interventions and in the design of studies to evaluate them. Several computational methods have been proposed to infer transmission chains from sequence data; however, existing methods do not generally reliably reconstruct transmission trees because genetic sequence data or inferred phylogenetic trees from such data contain insufficient information for accurate estimation of transmission chains. Here, we show by simulation studies that incorporating infection times, even when they are uncertain, can greatly improve the accuracy of reconstruction of transmission trees. To achieve this improvement

SUBMITTER: Montazeri H 

PROVIDER: S-EPMC8212962 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature