Dynamic intimate contact social networks and epidemic interventions Page: 14
The following text was automatically extracted from the image on this page using optical character recognition software:
14 C.D. Corley, A.R. Mikler, D.J. Cook and K. Singh
Statistic p(k) COSIM p(k) x COSIM
m 7693 7716 7742
8(G) 3.08-4 3.09E-4 3.10E-4
6(G*) 1.54E-4 1.54E-4 1.55E-4
cc(Males) 0.423 0.457 0.442
cc(Females) 0.218 0.250 0.233
cc(G) 0.321 0.353 0.337
cc1T(Males) 0.786 0.810 0.799
ccT (Females) 0.848 0.861 0.853
ccT(G) 0.817 0.835 0.826
ccT (Males) 0.456 0.486 0.470
ccT(Females) 0.226 0.255 0.241
cct(G) 0.321 0.370 0.337
Table 1 Generated Social Network Graph Statistics
lation. The simulator's parameter space is gathered from (Corley & Mikler 2005).
The demographic feature vectors are arbitrarily defined with five features, each
feature with a integer value between 0 and 4. The discrete values are drawn from
a uniform distribution. The use of a uniform distribution in the demographic fea-
tures translates to a psuedo-"random" mixing due to the homogeneous nature of
the population demographic strata composition. To determine the probability of
natural infection a binomial is calculated with the chance of infection in one en-
counter (pik) and the number of encounters (A) which occur (pn(i) = 1 - [1 - p);
similarly, the probability of breakthrough infection combines intervention efficacy
(eint) and chance of natural infection ( pb(i) = eint pik). The specific stochastic
disease parameters include the probability of acquiring HPV in one encounter (0.08
male-to-female, 0.02 female-to-male), encounter frequency drawn from a Poisson
distribution with a mean of 50, intervention efficacy is 75%, the age-range modeled
is 50 years, infection clears after two years and 5% of the population is initially
infected(Corley & Mikler 2005).
Population-level impact from three intervention strategies is evaluated; these in-
clude no intervention, vaccinating only males, and vaccinating only females. An in-
tervention targeting both males and females would be economically cost-prohibitive
and not included in our evaluations. Each Monte-Carlo simulation is loaded with
the parameter space described earlier, population size of 10,000 (IG, = Gfl),
and executed for 30 discrete realizations (years). The impact of each intervention
setting is averaged from ten Monte-Carlo simulations and the results are shown
in Fig.6. Intervention results are analyzed by the relative reduction in prevalence
(RRP) between no intervention and a specific strategy. Our results show a RRP of
75% (0.2 to 0.05 in female population) at the height of the epidemic when vacci-
nating females at 80% coverage and 75% efficacy. To date, no other social network
simulator solely built on heterosexual intimate contacts has been developed for in-
tervention analysis; however, much research has been conducted in this area using
intervention coverage is 80%.
Here’s what’s next.
This article can be searched. Note: Results may vary based on the legibility of text within the document.
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 Article.
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/m1/14/: accessed June 29, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.