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    Linking social and pathogen transmission networks using microbial genetics in giraffe (Giraffa cameJopardalis)

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    Date
    2013
    Author
    Atwill, Edward
    Isabel, Lynne A.
    McCowan, Brenda
    VanderWaal, Kimberly L.
    Type
    Article; en
    Language
    en
    Metadata
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    Abstract
    Although network analysis has drawn considerable attention as a promising tool for disease ecology, empirical research has been hindered by limitations in detecting the occurrence of pathogen transmission (who transmitted to whom) within social networks. 2. Using a novel approach, we utilize the genetics of a diverse microbe, Escherichia coli, to infer where direct or indirect transmission has occurred and use these data to construct transmission networks for a wild giraffe population (Giraffe camelopardalisi. Individuals were considered to be a part of the same transmission chain and were interlinked in the transmission network if they shared genetic subtypes of E. coli. 3. By using microbial genetics to quantify who transmits to whom independently from the behavioural data on who is in contact with whom, we were able to directly investigate how the structure of contact networks influences the structure of the transmission network. To distinguish between the effects of social and environmental contact on transmission dynamics, the transmission network was compared with two separate contact networks defined from the behavioural data: a social network based on association patterns, and a spatial network based on patterns of home-range overlap among individuals. 4. We found that links in the transmission network were more likely to occur between individuals that were strongly linked in the social network. Furthermore, individuals that had more numerous connections or that occupied 'bottleneck' positions in the social network tended to occupy similar positions in the transmission network. No similar correlations were observed between the spatial and transmission networks. This indicates that an individual's social network position is predictive of transmission network position, which has implications for identifying individuals that function as super-spreaders or transmission bottlenecks in the population.
    URI
    http://hdl.handle.net/11295/72381
    Citation
    Journal of Animal Ecology 2013
    Sponsorhip
    University of Nairobi
    Publisher
    British Ecological Society
    Subject
    wildlife disease
    space-use patterns
    Social Structure
    infection dynamics
    epidemiology
    disease ecology
    bacterial genotyping
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    • Faculty of Agriculture & Veterinary Medicine (FAg / FVM) [5481]

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