Journal article
Visualizing the impact of space-time uncertainties on dengue fever patterns
International journal of geographical information science : IJGIS, v 28(5), pp 1107-1127
04 May 2014
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
In this article, we evaluate the impact of positional and temporal inaccuracies on the mapping and detection of potential outbreaks of dengue fever in Cali, an urban environment of Colombia. Positional uncertainties in input data are determined by comparison between coordinates following an automated geocoding process and those extracted from on-field GPS measurements. Temporal uncertainties are modeled around the incubation period for dengue fever. To test the robustness of disease intensities in space and time when accounting for the potential space-time error, each dengue case is perturbed using Monte Carlo simulations. A space-time kernel density estimation (STKDE) is conducted on both perturbed and observed sets of dengue cases. To reduce the computational effort, we use a parallel spatial computing solution. The results are visualized in a 3D framework, which facilitates the discovery of new, significant space-time patterns and shapes of dengue outbreaks while enhancing our understanding of complex and uncertain dynamics of vector-borne diseases.
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Details
- Title
- Visualizing the impact of space-time uncertainties on dengue fever patterns
- Creators
- Eric Delmelle - University of North Carolina at CharlotteColine Dony - University of North Carolina at CharlotteIrene Casas - Louisiana Tech UniversityMeijuan Jia - University of North Carolina at CharlotteWenwu Tang - University of North Carolina at Charlotte
- Publication Details
- International journal of geographical information science : IJGIS, v 28(5), pp 1107-1127
- Publisher
- Taylor & Francis
- Number of pages
- 21
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Urban Health Collaborative
- Web of Science ID
- WOS:000334334400015
- Scopus ID
- 2-s2.0-84899125995
- Other Identifier
- 991021874424504721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Information Systems
- Geography
- Geography, Physical
- Information Science & Library Science