Unravelling transmission trees of infectious diseases by combining genetic and epidemiological data

Knowledge on the transmission tree of an epidemic can provide valuable insights into disease dynamics. The transmission tree can be reconstructed by analysing either detailed epidemiological data (e.g. contact tracing) or, if sufficient genetic diversity accumulates over the course of the epidemic,...

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Bibliographic Details
Published in:Proceedings of the Royal Society. B, Biological sciences Biological sciences, 2012-02, Vol.279 (1728), p.444-450
Main Authors: Ypma, R. J. F, Bataille, A. M. A, Stegeman, A, Koch, G, Wallinga, J, van Ballegooijen, W. M
Format: Article
Language:English
Subjects:
Animal Husbandry
Animals
Avian Influenza
Chickens
Consensus Sequence
Data transmission
Data types
Disease transmission
Ducks
Epidemics
Epidemics - veterinary
Epidemiology
farms
foot
genetic variation
h7n7
Hemagglutinins - genetics
Human genetics
Humans
Infections
Influenza A virus
Influenza A Virus, H7N7 Subtype - genetics
Influenza A Virus, H7N7 Subtype - physiology
Influenza in Birds - epidemiology
Influenza in Birds - transmission
Likelihood Functions
Markov Chains
Medical genetics
Molecular Epidemiology
Monte Carlo Method
mouth-disease
netherlands
Netherlands - epidemiology
Neuraminidase - genetics
outbreak
pathogens
poultry
RNA Replicase - genetics
Sequence Analysis, RNA - veterinary
Time Factors
Transmission Tree
Turkeys
Viral Proteins - genetics
Viruses
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Description
Summary:Knowledge on the transmission tree of an epidemic can provide valuable insights into disease dynamics. The transmission tree can be reconstructed by analysing either detailed epidemiological data (e.g. contact tracing) or, if sufficient genetic diversity accumulates over the course of the epidemic, genetic data of the pathogen. We present a likelihood-based framework to integrate these two data types, estimating probabilities of infection by taking weighted averages over the set of possible transmission trees. We test the approach by applying it to temporal, geographical and genetic data on the 241 poultry farms infected in an epidemic of avian influenza A (H7N7) in The Netherlands in 2003. We show that the combined approach estimates the transmission tree with higher correctness and resolution than analyses based on genetic or epidemiological data alone. Furthermore, the estimated tree reveals the relative infectiousness of farms of different types and sizes.
ISSN:0962-8452
1471-2954
1471-2945
DOI:10.1098/rspb.2011.0913