title: Reconstructing transmission trees for communicable diseases using densely sampled genetic data.
abstract: Whole genome sequencing of pathogens from multiple hosts in an epidemic offers the potential to investigate who infected whom with unparalleled resolution, potentially yielding important insights into disease dynamics and the impact of control measures. We considered disease outbreaks in a setting with dense genomic sampling, and formulated stochastic epidemic models to investigate person-to-person transmission, based on observed genomic and epidemiological data. We constructed models in which the genetic distance between sampled genotypes depends on the epidemiological relationship between the hosts. A data augmented Markov chain Monte Carlo algorithm was used to sample over the transmission trees, providing a posterior probability for any given transmission route. We investigated the predictive performance of our methodology using simulated data, demonstrating high sensitivity and specificity, particularly for rapidly mutating pathogens with low transmissibility. We then analyzed data collected during an outbreak of methicillin-resistantStaphylococcus aureusin a hospital, identifying probable transmission routes and estimating epidemiological parameters. Our approach overcomes limitations of previous methods, providing a framework with the flexibility to allow for unobserved infection times, multiple independent introductions of the pathogen, and within-host genetic diversity, as well as allowing forward simulation.
authors.affiliation: School of Mathematical Sciences, University of Nottingham, Nottingham, UK; Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, Boston, USA.
authors.forename: Colin J
authors.initials: CJ
authors.lastname: Worby
authors.affiliation: School of Mathematical Sciences, University of Nottingham, Nottingham, UK.
authors.forename: Philip D
authors.initials: PD
authors.lastname: O'Neill
authors.affiliation: School of Mathematical Sciences, University of Nottingham, Nottingham, UK.
authors.forename: Theodore
authors.initials: T
authors.lastname: Kypraios
authors.affiliation: Modelling & Economics Unit, Public Health England, London, UK.
authors.forename: Julie V
authors.initials: JV
authors.lastname: Robotham
authors.affiliation: MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
authors.forename: Daniela
authors.initials: D
authors.lastname: De Angelis
authors.affiliation: Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
authors.forename: Edward J P
authors.initials: EJ
authors.lastname: Cartwright
authors.affiliation: Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK; Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK.
authors.forename: Sharon J
authors.initials: SJ
authors.lastname: Peacock
authors.affiliation: Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK; Mahidol-Oxford Tropical Medicine Research Unit, Bangkok, Thailand.
authors.forename: Ben S
authors.initials: BS
authors.lastname: Cooper