A Bayesian inference method to estimate transmission trees with multiple introductions; applied to SARS-CoV-2 in Dutch mink farms
Knowledge of who infected whom during an outbreak of an infectious disease is important to determine risk factors for transmission and to design effective control measures. Both whole-genome sequencing of pathogens and epidemiological data provide useful information about the transmission events and underlying processes. Existing models to infer transmission trees usually assume that the pathogen is introduced only once from outside into the population of interest. However, this is not always true. For instance, SARS-CoV-2 is suggested to be introduced multiple times in mink farms in the Nethe... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2023 |
Reihe/Periodikum: | PLOS Computational Biology ; volume 19, issue 11, page e1010928 ; ISSN 1553-7358 |
Verlag/Hrsg.: |
Public Library of Science (PLoS)
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Schlagwörter: | Computational Theory and Mathematics / Cellular and Molecular Neuroscience / Genetics / Molecular Biology / Ecology / Modeling and Simulation / Evolution / Behavior and Systematics |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-27058455 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://dx.doi.org/10.1371/journal.pcbi.1010928 |