Epidemic centrality and the underestimated epidemic impact on network peripheral nodes

Details Epidemic centrality and the underestimated epidemic impact on network peripheral nodes Epidemic centrality and the underestimated epidemic impact on network peripheral nodes

2011-10-12

arxiv.org/abs/1110.2558v1

Physics

Physics and Society

Scientific paper

Studies of disease spreading on complex networks have provided a deep insight into the conditions of onset, dynamics and prevention of epidemics in human populations and malicious software propagation in computer networks. Identifying nodes which, when initially infected, infect the largest part of the network and ranking them according to their epidemic impact is a priority for public health policies. In simulations of the disease spreading in SIR model on studied empirical complex networks, it is shown that the ranking depends on the dynamical regime of the disease spreading. A possible mechanism leading to this dynamical dependence is illustrated in an analytically tractable example. A measure called epidemic centrality, averaging the epidemic impact over all possible disease spreading regimes, is introduced as a basis of epidemic ranking. Contrary to standard notion, the epidemic centrality of nodes with high degree, k-cores value or betweenness, which are structurally central, is comparable to epidemic centrality of structurally peripheral nodes. These findings indicate that the impact of an epidemic starting at structurally peripheral nodes may be considerably underestimated. Network periphery should gain a more prominent role in the allocation of resources in future epidemic preparedness plans.

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