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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

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.
Journal ArticleDOI

Statistical physics of social dynamics

TL;DR: In this article, a wide list of topics ranging from opinion and cultural and language dynamics to crowd behavior, hierarchy formation, human dynamics, and social spreading are reviewed and connections between these problems and other, more traditional, topics of statistical physics are highlighted.
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Evolution of networks

TL;DR: The recent rapid progress in the statistical physics of evolving networks is reviewed, and how growing networks self-organize into scale-free structures is discussed, and the role of the mechanism of preferential linking is investigated.
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Epidemic processes in complex networks

TL;DR: A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear.
References
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Journal ArticleDOI

An unsupervised method of classifying remotely sensed images using Kohonen self-organizing maps and agglomerative hierarchical clustering methods

TL;DR: The methodology proposed in this work attempts to take advantage of the properties of Kohonen's self‐organizing map (SOM) together with agglomerative hierarchical clustering methods to perform the automatic classification of remotely sensed images.
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High GUD Incidence in the Early 20th Century Created a Particularly Permissive Time Window for the Origin and Initial Spread of Epidemic HIV Strains

TL;DR: The results suggest that intense GUD in promiscuous urban communities was the main factor driving HIV emergence, and that the early 20th century was particularly permissive for the emergence of HIV by heterosexual transmission.

Mathematical Approaches to Infectious Disease Prediction and Control

TL;DR: In this paper, the authors introduce contact network epidemiology, a relatively new approach that applies bond percolation on random graphs to model the spread of infectious disease through het- erogeneous populations.
Journal ArticleDOI

The effect of network mixing patterns on epidemic dynamics and the efficacy of disease contact tracing.

TL;DR: Stochastic simulations are used to investigate the effects of mixing patterns on epidemic dynamics and contact-tracing efficacy, finding that for small epidemics, contact tracing is more effective on disassortative networks due to the greater resilience of assortative Networks to link removal.
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