Dynamic intimate contact social networks and epidemic interventions Page: 2
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2 C.D. Corley, A.R. Mikler, D.J. Cook and K. Singh
Computer Science at the University of North Texas (UNT) where he
holds the rank of associate professor in Computer Science with joint
appointment in the Department of Biological Sciences. His research
interests include: Computational Epidemiology, Distributed Coordina-
tion of Intelligent Mobile Agents, Distributed Decision Making, Multi-
Agent Simulation and Stochastic Cellular Automate. Dr. Mikler has
established and is the director of the Computational Epidemiology Re-
search Laboratory (CERL) which provides the necessary computational
infrastructure to conduct large scale simulations of Infectious Disease
Epidemics. As a member of the Institute of Applied Science at UNT,
he has been conducting collaborative and interdisciplinary research in
computational science, specifically in the areas of quantitative analysis
of ecological processes and Biocomplexity. Dr. Mikler is an associate
editor of the Telecommunication Systems Journal and a member of the
ACM and the IEEE Computer Society.
Dr. Diane J. Cook is a Huie-Rogers Chair Professor in the School of
Electrical Engineering and Computer Science at Washington State Uni-
versity. Dr. Cook received a B.S. degree in Math/Computer Science
from Wheaton College in 1985, a M.S. degree in Computer Science
from the University of Illinois in 1987, and a Ph.D. degree in Computer
Science from the University of Illinois in 1990. Her research interests
include artificial intelligence, machine learning, graph-based relational
data mining, smart environments, and robotics.
Dr. Karan P. Singh is Professor and Chair in the School of Public Health
Department of Biostatistics at University of North Texas Health Science
Center at Fort Worth University. Dr. Singh received a B.Sc. degree in
Mathematics, Physics and Chemistry from Meerut University (India) in
1975, a M.Sc. degree in Applied Statistics from the CCSHA University
(India) in 1977, a M. S. degree in Computational and Applied Mathe-
matics from the Old Dominion University in 1982, and a Ph.D. degree
in Statistics from the University of Memphis in 1986. His research in-
terests include mathematical modeling, longitudinal data analysis, sta-
tistical computing, survival methodology and health services research
Sexually transmitted diseases and infections are a significant and increasing
threat among both developed and developing countries around the world, causing
varying degrees of mortality and morbidity in all populations (Eames & Keeling
2002). The rates of prevalence of curable sexually transmitted diseases and in-
fections are highest among the most developed countries, with a quarter of these
conditions occurring within the 13-19 age range (Eng & Butler 1996). The respon-
sibility of halting the dissemination of these conditions lies upon the shoulders of
professionals within the public health industry. In order to properly and effectively
use funding and resources, these individuals must have reliable tools to help predict
the most appropriate means of intervention strategies.
Sexually transmitted diseases and infections are on the brink of becoming consid-
ered endemic within general populations. Many of these illnesses are preventable in
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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/m1/2/: accessed April 27, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.