Infection dynamics on scale-free networks.

By R. May, A. Lloyd. Physical review. E, Statistical, nonlinear, and soft matter physics, 2001

762 citations recorded by the source corpus.

Subfields: Experimental and Cognitive Psychology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/442a6f951160309c21e73b59ef3330320dca0bff

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In Experimental and Cognitive Psychology

In Statistical and Nonlinear Physics

Citations in the corpus

Modelling dynamical processes in complex socio-technical systems (2011, background): “Although this is not the case in any finite-size real-world network 50,51 , larger heterogeneity levels lead to smaller epidemic thresholds (Fig.”
Dynamical patterns of epidemic outbreaks in complex heterogeneous networks. (2004, neutral): “…infected individuals whatever the rate of infection characterizing the epidemic, eventually leading to the absence of any epidemic threshold below which the infection cannot initiate a major outbreak (Pastor- Satorras and Vespignani, 2001a,b; May and Lloyd, 2001; Moreno et al., 2002; Newman, 2001).”
The “New” Science of Networks (2004, background): “…(Liljeros et al. 2001), however, has subsequently been questioned (Jones & Handcock 2003), as has the absence of the epidemic threshold when factors such attenuation of infectiousness over time (Wu et al. 2004), and the ﬁnite size of real networks (May & Lloyd 2001) are taken into account.”
Graph theory and networks in Biology. (2006, methodology): “The same result was subsequently derived using different methods in [218].”
Adaptive coevolutionary networks: a review (2007, background): “For instance it was shown that vaccination of a fraction of the nodes cannot stop epidemics on a scale free network [44, 52].”
When individual behaviour matters: homogeneous and network models in epidemiology (2007, background): “The field has focused particularly on scale-free random networks ( May & Lloyd 2001; Dezso & Barabasi 2002; Pastor-Satorras & Vespignani 2002), based on the apparent ubiquity of such networks in natural and human-made systems and a (limited) set of studies of epidemiologically relevant contact patt”
Memory in network flows and its effects on spreading dynamics and community detection (2013, methodology): “community detection algorithms we developed for analyzing memory effects in the data; (5) we explain how we generalize commonly used compartmental models for spreading dynamics to include memory; and (6) we introduce a simple memory model for mechanistic understanding of memory effects. We have made”
The Structure and Function of Complex Networks (2003, result): “Since most power-law networks satisfy this condition, we expect diseases always to propagate in these networks, regardless of transmission probability between individuals, a point that was first made, in the context of models of computer virus epidemiology, by Pastor-Satorras and Vespignani [333, 33”
Statistical physics of vaccination (2016, background): “Spreading epidemics on complex networks has been studied by many researchers including May and Lloyd [222].”
Complex networks: small-world, scale-free and beyond (2003, neutral): “Recently, some researchers have started to study such spreading phenomena, for example on small-world and scale-free networks [29-34].”
A new route to the evolution of cooperation (2006, background): “At the heart of the theory, heterogeneity leads to an ubiquitous modification of the basic reproductive number R0, which ultimately defines the threshold for epidemic outbreaks (May, Gupta & McLean, 2001; Anderson & May, 1991, May & Lloyd, 2001 ).”