Social Network Simulation and Mining Social Media to Advance Epidemiology

Social Network Simulation and Mining Social Media to Advance Epidemiology

Date: August 2009
Creator: Corley, Courtney David
Description: Traditional Public Health decision-support can benefit from the Web and social media revolution. This dissertation presents approaches to mining social media benefiting public health epidemiology. Through discovery and analysis of trends in Influenza related blogs, a correlation to Centers for Disease Control and Prevention (CDC) influenza-like-illness patient reporting at sentinel health-care providers is verified. A second approach considers personal beliefs of vaccination in social media. A vaccine for human papillomavirus (HPV) was approved by the Food and Drug Administration in May 2006. The virus is present in nearly all cervical cancers and implicated in many throat and oral cancers. Results from automatic sentiment classification of HPV vaccination beliefs are presented which will enable more accurate prediction of the vaccine's population-level impact. Two epidemic models are introduced that embody the intimate social networks related to HPV transmission. Ultimately, aggregating these methodologies with epidemic and social network modeling facilitate effective development of strategies for targeted interventions.
Contributing Partner: UNT Libraries
Modeling the Impact and Intervention of a Sexually Transmitted Disease: Human Papilloma Virus

Modeling the Impact and Intervention of a Sexually Transmitted Disease: Human Papilloma Virus

Date: May 2006
Creator: Corley, Courtney D.
Description: Many human papilloma virus (HPV) types are sexually transmitted and HPV DNA types 16, 18, 31, and 45 account for more than 75% if all cervical dysplasia. Candidate vaccines are successfully completing US Federal Drug Agency (FDA) phase III testing and several drug companies are in licensing arbitration. Once this vaccine become available it is unlikely that 100% vaccination coverage will be probable; hence, the need for vaccination strategies that will have the greatest reduction on the endemic prevalence of HPV. This thesis introduces two discrete-time models for evaluating the effect of demographic-biased vaccination strategies: one model incorporates temporal demographics (i.e., age) in population compartments; the other non-temporal demographics (i.e., race, ethnicity). Also presented is an intuitive Web-based interface that was developed to allow the user to evaluate the effects on prevalence of a demographic-biased intervention by tailoring the model parameters to specific demographics and geographical region.
Contributing Partner: UNT Libraries
Measuring the Semantic Similarity of Texts

Measuring the Semantic Similarity of Texts

Date: June 2005
Creator: Corley, Courtney & Mihalcea, Rada, 1974-
Description: This paper discusses measuring the semantic similarity of texts.
Contributing Partner: UNT College of Engineering
Text Semantic Similarity, with Applications

Text Semantic Similarity, with Applications

Date: September 2005
Creator: Corley, Courtney; Csomai, Andras & Mihalcea, Rada, 1974-
Description: In this paper, the authors present a knowledge-based method for measuring the semantic-similarity of texts. Through experiments performed on two different applications: (1) paraphrase and entailment identification, and (2) word sense similarity, the authors show that this method outperforms the traditional text similarity metrics based on lexical matching.
Contributing Partner: UNT College of Engineering
Corpus-based and Knowledge-based Measures of Text Semantic Similarity

Corpus-based and Knowledge-based Measures of Text Semantic Similarity

Date: July 2006
Creator: Mihalcea, Rada, 1974-; Corley, Courtney & Strapparava, Carlo, 1962-
Description: This article discusses corpus-based and knowledge-based measures of text semantic similarity.
Contributing Partner: UNT College of Engineering
LESSONS LEARNED Biosurveillance Mobile App Development Intern Competition (Summer 2013)

LESSONS LEARNED Biosurveillance Mobile App Development Intern Competition (Summer 2013)

Date: January 14, 2014
Creator: Noonan, Christine F.; Henry, Michael J. & Corley, Courtney D.
Description: The purpose of the lessons learned document for the BEOWulf Biosurveillance Mobile App Development Intern Competition is to capture the project’s lessons learned in a formal document for use by other project managers on similar future projects. This document may be used as part of new project planning for similar projects in order to determine what problems occurred and how those problems were handled and may be avoided in the future. Additionally, this document details what went well with the project and why, so that other project managers may capitalize on these actions. Project managers may also use this document to determine who the project team members were in order to solicit feedback for planning their projects in the future. This document will be formally communicated with the organization and will become a part of the organizational assets and archives.
Contributing Partner: UNT Libraries Government Documents Department
Dynamic intimate contact social networks and epidemic interventions

Dynamic intimate contact social networks and epidemic interventions

Date: 2008
Creator: Corley, Courtney; Mikler, Armin R.; Cook, Diane J., 1963- & Singh, Karan P.
Description: This article discusses dynamic intimate contact social networks and epidemic interventions.
Contributing Partner: UNT College of Engineering
Text and Structural Data Mining of Influenza Mentions in Web and Social Media

Text and Structural Data Mining of Influenza Mentions in Web and Social Media

Date: February 22, 2010
Creator: Corley, Courtney; Cook, Diane J., 1963-; Mikler, Armin R. & Singh, Karan P.
Description: This article discusses text and structural data mining of influenza mentions in web and social media.
Contributing Partner: UNT College of Engineering
BioCat 2.0

BioCat 2.0

Date: September 16, 2013
Creator: Corley, Courtney D.; Noonan, Christine F.; Bartholomew, Rachel A.; Franklin, Trisha L.; Hutchison, Janine R.; Lancaster, Mary J. et al.
Description: The U.S. Department of Homeland Security (DHS) National Biosurveillance Integration Center (NBIC) was established in 2008 with a primary mission to “(1) enhance the capability of the Federal Government to (A) rapidly identify, characterize, localize, and track a biological event of national concern by integrating and analyzing data relating to human health, animal, plant, food, and environmental monitoring systems (both national and international); and (B) disseminate alerts and other information to Member Agencies and, in coordination with (and where possible through) Member Agencies, to agencies of State, local, and tribal governments, as appropriate, to enhance the ability of such agencies to respond to a biological event of national concern; and (2) oversee development and operation of the National Biosurveillance Integration System (NBIS).” Inherent in its mission then and the broader NBIS, NBIC is concerned with the identification, understanding, and use of a variety of biosurveillance models and systems. The goal of this project is to characterize, evaluate, classify, and catalog existing disease forecast and prediction models that could provide operational decision support for recognizing a biological event having a potentially significant impact. Additionally, gaps should be identified and recommendations made on using disease models in an operational environment to support ...
Contributing Partner: UNT Libraries Government Documents Department
An Approach for Assessing the Signature Quality of Various Chemical Assays when Predicting the Culture Media Used to Grow Microorganisms

An Approach for Assessing the Signature Quality of Various Chemical Assays when Predicting the Culture Media Used to Grow Microorganisms

Date: February 1, 2013
Creator: Holmes, Aimee E.; Sego, Landon H.; Webb-Robertson, Bobbie-Jo M.; Kreuzer, Helen W.; Anderson, Richard M.; Unwin, Stephen D. et al.
Description: We demonstrate an approach for assessing the quality of a signature system designed to predict the culture medium used to grow a microorganism. The system was comprised of four chemical assays designed to identify various ingredients that could be used to produce the culture medium. The analytical measurements resulting from any combination of these four assays can be used in a Bayesian network to predict the probabilities that the microorganism was grown using one of eleven culture media. We evaluated combinations of the signature system by removing one or more of the assays from the Bayes network. We measured and compared the quality of the various Bayes nets in terms of fidelity, cost, risk, and utility, a method we refer to as Signature Quality Metrics
Contributing Partner: UNT Libraries Government Documents Department