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Open AccessJournal ArticleDOI

The Web of Human Sexual Contacts

TLDR
In this article, the authors analyze data on the sexual behavior of a random sample of individuals, and find that the cumulative distributions of the number of sexual partners during the twelve months prior to the survey decays as a power law with similar exponents for females and males.
Abstract
Many ``real-world'' networks are clearly defined while most ``social'' networks are to some extent subjective. Indeed, the accuracy of empirically-determined social networks is a question of some concern because individuals may have distinct perceptions of what constitutes a social link. One unambiguous type of connection is sexual contact. Here we analyze data on the sexual behavior of a random sample of individuals, and find that the cumulative distributions of the number of sexual partners during the twelve months prior to the survey decays as a power law with similar exponents $\alpha \approx 2.4$ for females and males. The scale-free nature of the web of human sexual contacts suggests that strategic interventions aimed at preventing the spread of sexually-transmitted diseases may be the most efficient approach.

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Citations
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Journal ArticleDOI

Edge-based compartmental modelling for infectious disease spread

TL;DR: This study introduces edge-based compartmental modelling, a technique eliminating assumptions about how contact rates are distributed and how long partnerships last, and derives simple ordinary differential equation models capturing social heterogeneity (heterogeneous contact rates) while explicitly considering the impact of partnership duration.
Posted Content

SIR dynamics in random networks with heterogeneous connectivity

TL;DR: In this paper, the SIR dynamics can be modeled with a system of three nonlinear ODE's, which makes use of the probability generating function (PGF) formalism for representing the degree distribution of a random network.
Journal ArticleDOI

Behaviors of susceptible-infected epidemics on scale-free networks with identical infectivity.

TL;DR: A susceptible-infected model with identical infectivity, in which, at every time step, each node can only contact a constant number of neighbors is proposed, which indicates the existence of an essential relationship between network traffic and network epidemic on scale-free networks.
Book ChapterDOI

Epidemics and immunization in scale‐free networks

TL;DR: The authors offer concepts to model network structures and dynamics, focussing on approaches applicable across disciplines, and focus on networks that change their topology as in morphogenesis and self-organization.
Journal ArticleDOI

Stability and topology of scale-free networks under attack and defense strategies.

TL;DR: It is found that, for an intentional attack, little knowledge of the well-connected sites is sufficient to strongly reduce p(c), and at criticality, the topology of the network depends on the removal strategy, implying that different strategies may lead to different kinds of percolation transitions.
References
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Journal ArticleDOI

Collective dynamics of small-world networks

TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Journal ArticleDOI

Emergence of Scaling in Random Networks

TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
Journal ArticleDOI

Statistical mechanics of complex networks

TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
Journal ArticleDOI

The Structure and Function of Complex Networks

Mark Newman
- 01 Jan 2003 - 
TL;DR: Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Journal ArticleDOI

Complex networks: Structure and dynamics

TL;DR: The major concepts and results recently achieved in the study of the structure and dynamics of complex networks are reviewed, and the relevant applications of these ideas in many different disciplines are summarized, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.
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