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, 2, 235-45

Networks and the Ecology of Parasite Transmission: A Framework for Wildlife Parasitology


Networks and the Ecology of Parasite Transmission: A Framework for Wildlife Parasitology

Stephanie S Godfrey. Int J Parasitol Parasites Wildl.


Social network analysis has recently emerged as a popular tool for understanding disease transmission in host populations. Although social networks have most extensively been applied to modelling the transmission of diseases through human populations, more recently the method has been applied to wildlife populations. The majority of examples from wildlife involve modelling the transmission of contagious microbes (mainly viruses and bacteria), normally in context of understanding wildlife disease epidemics. However, a growing number of studies have used networks to explore the ecology of parasite transmission in wildlife populations for a range of endemic parasites representing a diversity of life cycles and transmission methods. This review addresses the application of network models in representing the transmission of parasites with more complex life cycles, and illustrates the way in which this approach can be used to answer ecological questions about the transmission of parasites in wildlife populations.

Keywords: Animal behaviour; Conservation; Ecology; Male-bias parasite burdens; Parasite transmission; Social network; Sociality.


Fig. 1
Fig. 1
What is a network? A network in its most elementary form is an adjacency matrix, where row and column labels represent the individuals in the network, and the remaining cells represent the pair-wise associations among individuals in the network (panel A). These associations can be weighted, as below (panel A), where stronger relationships are assigned a higher value (for example, the duration or frequency of contact). They can also be directed, to reflect the direction of the association; in this instance, the direction of possible parasite transmission. In this case, rows represent donor nodes, and columns represent recipient nodes (e.g., in panel A: from node C (donor) to node D (recipient), there is a score of 1). The matrix can be visualised as a network diagram (panel B), consisting of nodes, which represent the epidemiological unit of interest (usually individuals) connected together by a series of edges representing the measure of association (the potential for parasite transmission). In context of understanding the ecology of parasite transmission, edges represent a ‘contact’ between two hosts that provides an opportunity for parasite transfer. The weighting of edges represents the likelihood of parasite transmission (e.g., the frequency or intensity of contact among hosts). The definition of a contact will depend on the type of parasite considered, and how it is passed from one host to another.
Fig. 2
Fig. 2
How do we use networks to understand the ecology of parasite transmission? Networks allow us to describe how the behaviour of individuals collectively affects the transmission of parasites within wildlife populations. They provide a flexible framework that enables analysis at three different levels; individual (panel A), dyadic (pair-wise associations) (panel B) and the network (population) level (panel C). Within each level of analysis, there are different metrics and analytical approaches that can be used to explore the ecology of parasite transmission.

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    1. Alexander R.D. The evolution of social behavior. Annu. Rev. Ecol. Syst. 1974;5:325–383.
    1. Altizer S., Nunn C.L., Thrall P.H., Gittleman J.L., Antonovics J., Cunningham A.A., Dobson A.P., Ezenwa V.O., Jones K.E., Pedersen A.B., Poss M., Pulliam J.R.C. Social organization and parasite risk in mammals: integrating theory and empirical studies. Annu. Rev. Ecol. Evol. Syst. 2003;34:517–547.
    1. Anderson R.M., May R.M. Populations biology of infectious diseases: part I. Nature. 1979;280:361–367. - PubMed
    1. Archie E.A., Luikart G., Ezenwa V.O. Infecting epidemiology with genetics: a new frontier in disease ecology. Trends Ecol. Evol. 2009;24:21–30. - PubMed
    1. Arnold W., Anja V.L. Ectoparasite loads decrease the fitness of alpine marmots (Marmota marmota) but are not a cost of sociality. Behav. Ecol. 1993;4:36–39.

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