The Influence of Social Network Graph Structure on Disease Dynamics in a Simulated Environment Page: 52
The following text was automatically extracted from the image on this page using optical character recognition software:
portion of the population became infected. This chapter analyzes the effectiveness of various vac-
cination strategies based on modifications of the centrality measures discussed in Section 2.4.3.
Experimentation follows the steps below which are repeated over various graph structures and
includes several vaccination policies for each distinct graph structure.
(i) Create a graph-based social network utilizing parameters given in Table 4.1.
(ii) Vaccinate individuals in the population.
(iii) Simulate multiple outbreaks in the established social network and collect data to assess
the severity of the outbreaks.
In contrast to the experiments presented in Chapter 3, the contact graphs are generated prior to
each outbreak to allow targeted vaccination of specific nodes based on centrality. The same contact
graphs are utilized for each vaccination policy and outbreak simulation. Statistics are recorded for
each simulation, including values of Ro0, duration, and the proportion of the population infected.
Comparisons of each indicator are presented in Section 4.4.
4.1. Creating a Social Network Graph
A population of size N is represented as a graph G(V, E) in which each vertex in the graph,
v e V, represents an individual and each edge in the graph, e(v, w) E E represents a contact
between two individuals. Each individual is labeled with a unique identification number between
0 and n - 1, inclusive, and Node n - 1 is adjacent to Node 0. Each member of the population has
an assigned neighborhood of size k, such that the neighborhood extends k/2 to the left and k/2 to
the right of that individual.
The contact graph is established based on the parameters listed in Table 4.1. Specific values
for these parameters are discussed in Section 4.3. The total number of contacts for the entire
population is calculated as the size of the population, N, times the average number of contacts
per person, per day, CR. The procedure of building the contact graph continues until the total
number of contacts has been exhausted. The algorithm for creating the contact graph is outlined in
Here’s what’s next.
This dissertation can be searched. Note: Results may vary based on the legibility of text within the document.
Tools / Downloads
Get a copy of this page or view the extracted text.
Citing and Sharing
Basic information for referencing this web page. We also provide extended guidance on usage rights, references, copying or embedding.
Reference the current page of this Dissertation.
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/m1/62/: accessed May 19, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; .