Search Results

Sociodemographic characteristics and sexual behavior as risk factors for human papillomavirus infection in Saudi Arabia

Description: This article seeks to determine the prevalence and the sociodemographic characteristics and sexual behavior risk factors for human papillomavirus (HPV) infection in a hospital-based cohort of women in Saudi Arabia.
Date: April 3, 2016
Creator: Alhamlan, F.S.; Khayat, H.H.; Ramisetty-Mikler, Suhasini; Al-Muammar, T.A.; Tulbah, A.M.; Al-Badawi, I.A. et al.
Item Type: Article
Partner: UNT College of Information

Quantifying Access Disparities in Response Plans

Description: This article develops and explores data driven methods to quantify vulnerabilities in the context of response plans, addressing limitations on the availability, granularity, and currency of data to identify vulnerable populations.
Date: January 15, 2016
Creator: Indrakanti, Saratchandra; Mikler, Armin R.; O'Neil II, Martin & Tiwari, Chetan
Item Type: Article
Partner: UNT College of Engineering

A Computational Methodology for Addressing Differentiated Access of Vulnerable Populations During Biological Emergencies

Description: Mitigation response plans must be created to protect affected populations during biological emergencies resulting from the release of harmful biochemical substances. Medical countermeasures have been stockpiled by the federal government for such emergencies. However, it is the responsibility of local governments to maintain solid, functional plans to apply these countermeasures to the entire target population within short, mandated time frames. Further, vulnerabilities in the population may serve as barriers preventing certain individuals from participating in mitigation activities. Therefore, functional response plans must be capable of reaching vulnerable populations.Transportation vulnerability results from lack of access to transportation. Transportation vulnerable populations located too far from mitigation resources are at-risk of not being able to participate in mitigation activities. Quantification of these populations requires the development of computational methods to integrate spatial demographic data and transportation resource data from disparate sources into the context of planned mitigation efforts. Research described in this dissertation focuses on quantifying transportation vulnerable populations and maximizing participation in response efforts. Algorithms developed as part of this research are integrated into a computational framework to promote a transition from research and development to deployment and use by biological emergency planners.
Date: August 2014
Creator: O’Neill II, Martin Joseph
Partner: UNT Libraries

UNT Research, Volume 23, 2014

Description: UNT Research magazine includes articles and notes about research at University of North Texas in various academic fields.
Date: 2014
Creator: University of North Texas
Partner: University Relations, Communications & Marketing department for UNT

Computational Methods for Vulnerability Analysis and Resource Allocation in Public Health Emergencies

Description: POD (Point of Dispensing)-based emergency response plans involving mass prophylaxis may seem feasible when considering the choice of dispensing points within a region, overall population density, and estimated traffic demands. However, the plan may fail to serve particular vulnerable sub-populations, resulting in access disparities during emergency response. Federal authorities emphasize on the need to identify sub-populations that cannot avail regular services during an emergency due to their special needs to ensure effective response. Vulnerable individuals require the targeted allocation of appropriate resources to serve their special needs. Devising schemes to address the needs of vulnerable sub-populations is essential for the effectiveness of response plans. This research focuses on data-driven computational methods to quantify and address vulnerabilities in response plans that require the allocation of targeted resources. Data-driven methods to identify and quantify vulnerabilities in response plans are developed as part of this research. Addressing vulnerabilities requires the targeted allocation of appropriate resources to PODs. The problem of resource allocation to PODs during public health emergencies is introduced and the variants of the resource allocation problem such as the spatial allocation, spatio-temporal allocation and optimal resource subset variants are formulated. Generating optimal resource allocation and scheduling solutions can be computationally hard problems. The application of metaheuristic techniques to find near-optimal solutions to the resource allocation problem in response plans is investigated. A vulnerability analysis and resource allocation framework that facilitates the demographic analysis of population data in the context of response plans, and the optimal allocation of resources with respect to the analysis are described.
Date: August 2015
Creator: Indrakanti, Saratchandra
Partner: UNT Libraries

UNT Research, Volume 19, 2010

Description: UNT Research magazine includes articles and notes about research at University of North Texas in various academic fields.
Date: 2010
Creator: University of North Texas
Partner: University Relations, Communications & Marketing department for UNT

UNT Research, Volume 22, 2013

Description: UNT Research magazine includes articles and notes about research at University of North Texas in various academic fields.
Date: 2013
Creator: University of North Texas
Partner: University Relations, Communications & Marketing department for UNT

Spatially Explicit Modeling of West Nile Virus Risk Using Environmental Data

Description: West Nile virus (WNV) is an emerging infectious disease that has widespread implications for public health practitioners across the world. Within a few years of its arrival in the United States the virus had spread across the North American continent. This research focuses on the development of a spatially explicit GIS-based predictive epidemiological model based on suitable environmental factors. We examined eleven commonly mapped environmental factors using both ordinary least squares regression (OLS) and geographically weighted regression (GWR). The GWR model was utilized to ascertain the impact of environmental factors on WNV risk patterns without the confounding effects of spatial non-stationarity that exist between place and health. It identifies the important underlying environmental factors related to suitable mosquito habitat conditions to make meaningful and spatially explicit predictions. Our model represents a multi-criteria decision analysis approach to create disease risk maps under data sparse situations. The best fitting model with an adjusted R2 of 0.71 revealed a strong association between WNV infection risk and a subset of environmental risk factors including road density, stream density, and land surface temperature. This research also postulates that understanding the underlying place characteristics and population composition for the occurrence of WNV infection is important for mitigating future outbreaks. While many spatial and aspatial models have attempted to predict the risk of WNV transmission, efforts to link these factors within a GIS framework are limited. One of the major challenges for such integration is the high dimensionality and large volumes typically associated with such models and data. This research uses a spatially explicit, multivariate geovisualization framework to integrate an environmental model of mosquito habitat with human risk factors derived from socio-economic and demographic variables. Our results show that such an integrated approach facilitates the exploratory analysis of complex data and supports reasoning about the underlying spatial ...
Date: December 2015
Creator: Kala, Abhishek K.
Partner: UNT Libraries

Catalog of the University of North Texas, 2010-2011, Graduate

Description: The UNT Graduate Bulletin includes information about class offerings as well as "policies, regulations, procedures and fees in effect at the time [the] publication went to press" (p. 1). Index starts on page 494.
Date: July 2010
Creator: University of North Texas
Item Type: Book
Partner: UNT Libraries