The Influence of Social Network Graph Structure on Disease Dynamics in a Simulated Environment Page: 65
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The average means and standard deviations for transmission centrality over population sizes 50,
150, and 250 are given in Table 4.4. Unlike the average contact centrality, the average transmission
centrality does not remain consistent within a given population size. As the probability of non-local
contacts increases, the average transmission centrality decreases. Comparing the transmission
centrality among the three populations sizes, it is noted that when p = 0 (all contacts are local),
the transmission centrality is very similar regardless of the population size. However, for p > 0,
these values do not remain consistent over the various population sizes.
The average means and standard deviations for spread centrality over population sizes 50,
150, and 250 are given in Table 4.5. The average mean spread centrality tends to increase as the
probability of non-local contacts increases from the lower values, p = 0 and p = 0.01 to the larger
values, p = 0.25 and p = 0.5, although in every case there is a slight drop in spread centrality
from p = 0.25 to p = 0.5. This is an interesting point, suggesting that spread centrality may reach
a peak in a small-world graph in which p has a value somewhere between p = 1% and p = 50%.
Although outside the realm of this study, this result indicates that further investigation is warranted
in this area.
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Johnson, Tina V. The Influence of Social Network Graph Structure on Disease Dynamics in a Simulated Environment, dissertation, December 2010; Denton, Texas. (https://digital.library.unt.edu/ark:/67531/metadc33173/m1/75/: accessed May 24, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; .