The Influence of Social Network Graph Structure on Disease Dynamics in a Simulated Environment Page: 6
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1.3. Disease Dynamics
Is it possible to precisely measure the severity of an epidemic or pandemic? What gauge can
be used to determine that an outbreak at a particular time and place is more destructive than one
at another time and/or location? Because parameters change from one occurrence to another, it
may be impossible to make an entirely valid comparison between two distinct outbreaks. There
are, however, indicators that are widely accepted as epidemiologic quantifiers. Even though these
standards may not provide a completely unbiased account for comparison, they do provide a metric
One quantifier often referred to in disease-related literature is the basic reproduction number,
Ro [6, 7, 19, 39, 67]. Ro, as formally defined in Section 2.3, is the expected average number of
secondary infections by a single infectious individual in a completely susceptible population. It is
an epidemic threshold that is measured at the beginning of an outbreak at a time when the majority
of the population is susceptible. Ro provides an indication how quickly an infection will spread.
Because Ro0 is based on secondary infections, larger values of Ro0 suggest a higher probability that
an outbreak will progress into an epidemic or pandemic. After an epidemic/pandemic has run its
course, the duration of the outbreak and the total number and proportion of individuals infected
can also be considered. In a simulated environment, these values can be measured and compared
from one outbreak to another.
1.4. Social Networks and Graph Theory
Graphs are exceptionally useful tools for analyzing social networks . In the study of graph
theory, graphs are represented by a set of vertices and a set of edges such that the edges represent
an association between two vertices . In a social network, the vertices represent individuals
or groups of individuals and the edges represent some sort of connection between two people or
two groups. There are many advantages to using graphs to analyze social networks, including an
established vocabulary, mathematical operations, and the ability to use and prove theorems about
graphs that can be transferred to the social structure .
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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/m1/16/: accessed May 19, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; .