Dynamic intimate contact social networks and epidemic interventions Page: 13
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Dynamic intimate contact social networks and epidemic interventions
Cumulative Distribution of Intimate Contacts
> X +.
1 10 100
Number of intimate partner changes per year
Figure 5 Cumulative Distribution for Intimate Contacts
feature vector cosine similarity, solely preferential attachment, and the aggregate of
preferential attachment and cosine similarity scoring. The graph statistics resulting
from the Monte-Carlo simulations are displayed in Table 1. The results demonstrate
the likelihood of clusters in our networks. They also show the range of clustering
coefficients for the graph and each bipartition subset. Each specific clustering co-
efficient statistic show a high occurrence of clusters compared to the density of G
and G*. An interesting observation from the table is that preferential attachment
alone, produces less neighborhood overlap compared to demographic feature cosine
similarity. This correlates to results from comparing clustering in social networks to
that of non-human networks where interactions are defined more by network topol-
ogy than other affinity measures; for instance, the Internet topology compared to
the Live-Journal community (Kumar, Novak, Raghavan & Tomkins 2004). Cen-
trality measures are valuable in quantifying network topologies; evaluating these
metrics on dynamic and evolving networks is an open research question and the
authors leave centrality evaluation to future work (Berger-Wolf & Saia 2006).
Quantitative analysis of DynSNIC's infection dynamic capabilities, in conjunc-
tion with health policies and interventions strategies, is provided in the following
case study. Many Human Papilloma Virus (HPV) types are sexually transmitted
and HPV DNA is found in 99.7% of all cervical cancers with HPV-types 16, 18, 31
and 45 accounting for 75% of cervical dysplasia(Goldie, Kohli & Grima 2004). Upon
acquisition of the HPV virus, the host could be asymptomatic for many years, clear
the infection, or cervical dysplasia could develop. HPV prevalence is an integral
component of cervical cancer's etiology; although, DynSNIC's vertex finite state
machine is also capable of representing additional states beyond infection status,
such as temporal pathogen dynamics (carcinogenesis). Presently, each vertex state
machine in DynSNIC label HPV's presence, susceptibility, or immunity (vaccina-
tion, other intervention or through cleared infection) in the host. We evaluate the
impact of several disparate intervention strategies on HPV prevalence in the popu-
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Corley, Courtney; Mikler, Armin R.; Cook, Diane J., 1963- & Singh, Karan P. Dynamic intimate contact social networks and epidemic interventions, article, 2008; [Geneva, Switzerland]. (digital.library.unt.edu/ark:/67531/metadc132993/m1/13/: accessed April 26, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.