Golden Software customers possess a broad assortment of backgrounds from earth sciences and engineering to education and politics. This vast background results in a variety of uses for Golden Software's products. Each customer uses the software in a unique way, and we are pleased to share these stories. This blog article features Dr. Eric Delmelle, a professor of GIS and Health Geography in the Department of Geography and Earth Sciences at the University of North Carolina, and his use of Voxler, among other applications, to visualize space-time patterns of human behaviors and human health issues.
Dr. Delmelle's research focuses on answering fundamental epidemiological questions where spatial and spatiotemporal methodology is a critical avenue for analysis. He uses robust geocomputational methodologies that "deepen our understanding on the dynamics of infectious and non-infectious diseases". Dr. Delmelle is dedicated to the development of new visualization techniques that detect space-time patterns at different scales and leverage state of the art computational techniques to generate predictive models that could ultimately have influence on health decisions in the public sector.
A great recent example of Dr. Delmelle's work was based around evaluating the impact of space-time patterns of dengue fever outbreaks in Cali, Colombia. Dr. Delmelle and his colleagues were recently published in the International Journal of Geographical Information Science, in an article titled, "Visualizing the impact of space-time uncertainties on dengue fever patterns". In their study, the group used Voxler's robust 3D display capabilities to visualize their results in a 3D framework, which aided in the discovery of new space-time patterns of dengue fever outbreaks and gave insight on the dynamics of vector-borne diseases.
Dengue fever is transmitted to humans by mosquitos in warm climates, often causing severe outbreaks in an area's populations and considered a serious health problem for problematic areas like Cali, Columbia. In Dr. Delmelle's research, fever cases were collected using georeferenced locations during an epidemic in 2010. Data clusters were generated from the collected cases over a 6-month period and visualized by Dr. Delmelle using a space-time kernel density estimation technique in Voxler. In the images below, Dr. Delmelle models the space-time kernel density estimation in Voxler of geocoded dengue fever cases reported in the 6-month study period with reference to the geographic area of study. The density of fever cases is rendered using VolRender modules and the highest density cases are highlighted in purple. Isosurface module "shells" are generated to delineate the highest densities of the reported cases across Cali.
Dr. Delmelle's 3D results of the space-time kernel density estimation of dengue fever outbreaks in Cali, Columbia. The highest density values are shown in purple.
The 3D visualization of the findings of Dr. Delmelle's research in Voxler resulted in being beneficial in a number of different ways. First, by mapping the 3D shape of the clusters, the dynamics of the dengue fever outbreak over time become more clear, which leads to a better understanding of the geographical pattern of the fever outbreak in terms of resurgence and eradication. The geocoding and temporal visualization of the fever data can "provide a better confidence for public health managers to decide where and when to allocate resources".
We are pleased Dr. Delmelle has integrated Voxler into his development of new visualization techniques for space-time data, and it's exciting to see his application of Voxler's tools in his work. You can find links to Dr. Delmelle's work in "Visualizing the impact of space-time uncertainties on dengue fever patterns" in the International Journal of Geographical Information Science, 28(5), 1107-1127.
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