Epidemic potential by sexual activity distributions.
Abstract
For sexually transmitted infections like HIV to propagate through a population, there
must be a path linking susceptible cases to currently infectious cases. The existence
of such paths depends in part on thedegree distribution.Here, we use simulation methods
to examine how two features of the degree distribution affect network connectivity:
Mean degree captures a volume dimension, while the skewness of the upper tail captures
a shape dimension. We find a clear interaction between shape and volume: When mean
degree is low, connectivity is greater for long-tailed distributions, but at higher
mean degree, connectivity is greater in short-tailed distributions. The phase transition
to a giant component and giant bicomponent emerges as a positive function of volume,
but it rises more sharply and ultimately reaches more people in short-tail distributions
than in long-tail distributions. These findings suggest that any interventions should
be attuned to how practices affect both the volume and shape of the degree distribution,
noting potential unanticipated effects. For example, policies that primarily affect
high-volume nodes may not be effective if they simply redistribute volume among lower
degree actors, which appears to exacerbate underlying network connectivity.
Type
Journal articleSubject
cohesionconnectivity
degree distributions
dynamic network diffusion
sexually transmitted infections
simulation
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https://hdl.handle.net/10161/16104Published Version (Please cite this version)
10.1017/nws.2017.3Publication Info
Moody, James; Adams, Jimi; & Morris, Martina (2017). Epidemic potential by sexual activity distributions. Netw Sci (Camb Univ Press), 5(4). pp. 461-475. 10.1017/nws.2017.3. Retrieved from https://hdl.handle.net/10161/16104.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
James Moody
Professor in the Department of Sociology
James Moody is the Robert O. Keohane professor of sociology at Duke University. He
has published extensively in the field of social networks, methods, and social theory.
His work has focused theoretically on the network foundations of social cohesion and
diffusion, with a particular emphasis on building tools and methods for understanding
dynamic social networks. He has used network models to help understand school racial
segregation, adolescent health, disease spread, economic development, a

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