The number of links to and from the starting node as a predictor of epidemic size in small-size directed networks |
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Authors: | Marco Pautasso Mathieu Moslonka-Lefebvre Michael J. Jeger |
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Affiliation: | 1. National ICT Australia (NICTA), RMIT University, School of Computer Science and IT, Melbourne, VIC 3001, Australia;2. RMIT University, School of Computer Science and IT, Melbourne, VIC 3001, Australia;3. School of Computer Science, University of Oklahoma, Norman, OK 73019-6151,nUnited States |
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Abstract: | Much recent modelling is focusing on epidemics in large-scale complex networks. Whether or not findings of these investigations also apply to networks of small size is still an open question. This is an important gap for many biological applications, including the spread of the oomycete pathogen Phytophthora ramorum in networks of plant nurseries. We use numerical simulations of disease spread and establishment in directed networks of 100 individual nodes at four levels of connectivity. Factors governing epidemic spread are network structure (local, small-world, random, scale-free) and the probabilities of infection persistence in a node and of infection transmission between connected nodes. Epidemic final size at equilibrium varies widely depending on the starting node of infection, although the latter does not affect the threshold condition for spread. The number of links from (out-degree) but not the number of links to (in-degree) the starting node of the epidemic explains a substantial amount of variation in final epidemic size at equilibrium irrespective of the structure of the network. The proportion of variance in epidemic size explained by the out-degree of the starting node increases with the level of connectivity. Targeting highly connected nodes is thus likely to make disease control more effective also in case of small-size populations, a result of relevance not just for the horticultural trade, but for epidemiology in general. |
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