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.read more
Citations
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Generating simple random graphs with prescribed degree distribution
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Maximal planar networks with large clustering coefficient and power-law degree distribution.
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Text and Structural Data Mining of Influenza Mentions in Web and Social Media
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Disease evolution on networks: the role of contact structure.
TL;DR: This paper investigates how a disease may adapt in response to the routes of transmission available between infected and susceptible individuals, using a computer–generated contact network to define potential transmission routes.
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Sexual network structure and the spread of HIV in Africa: evidence from Likoma Island, Malawi.
TL;DR: Contrary to claims that sexual networks in rural sub-Saharan Africa are too sparse to sustain generalized HIV epidemics, the structure of the networks observed in Likoma appears compatible with a broad diffusion of HIV among lower-risk groups.
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