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...

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Veröffentlicht in:	PLoS computational biology 2023-11, Vol.19 (11), p.e1010928-e1010928
Hauptverfasser:	Van der Roest, Bastiaan R, Bootsma, Martin C J, Fischer, Egil A J, Klinkenberg, Don, Kretzschmar, Mirjam E E
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Analysis Animals Bayes Theorem Bayesian analysis Bayesian statistical decision theory Control COVID-19 COVID-19 - epidemiology Disease transmission Diseases and pests DNA sequencing Epidemics Epidemiology Farms Foot & mouth disease Gene sequencing Genomes Genomics Health aspects Humans Infection control Infections Infectious diseases Information sources Mathematical models Methods Mink Minks Mutation Netherlands Nucleotide sequencing Outbreaks Pandemics Pathogens Phylogenetics Phylogeny Public health Risk factors SARS-CoV-2 - genetics Severe acute respiratory syndrome coronavirus 2 Statistical inference Viral diseases Whole genome sequencing
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