Advanced computational capabilities that emerged through continuous technological development have transformed many scientific disciplines, including the domain of health and medical geography. Today, scientists tackle computational challenges that used to be virtually impossible to solve, because 1) our ability to collect and store health-related data has improved substantially, and 2) analytical methods for solving scientific problems can now be applied on a massive scale. Therefore, the spatiotemporal analysis and modelling of health-related issues has experienced and driven fundamental changes.
The goal of this session is to create a platform for presenting and stimulating discussion about: accomplishments and remaining challenges of intersecting health and medical geography with cyberinfrastructure within a spatiotemporal context.
Topics may include, but are not limited to:
1. Disease Mapping: spatial and/or spatiotemporal analysis and visualization;
2. Disparities in health care accessibility;
3. Stochastic methods for assessing the significance of observed disease patterns;
4. Spatially explicit disease modeling (retrospective or prospective);
5. The use of cyber-enabled technologies (e.g., high performance computing, cloud computing) to analyze complex and massive spatiotemporal data for the discovery of relationships between health and environment.
Sponsor Groups: Spatial Analysis and Modeling Specialty Group, Cyberinfrastructure Specialty Group, Health and Medical Geography Specialty Group
Discussant: Dr. Xun Shi (Dartmouth)
|Presenter||Fahui Wang*, Lousiana State University, Jing Luo, Central China Normal University, Two-Step Optimization for Spatial Accessibility Improvement: A Case Study of Health Care Planning in Rural China||20||8:00 AM|
|Presenter||Michael Tiefelsdorf*, U of Texas at Dallas, Xiaojun Pu, U of Texas at Dallas, A simulation based investigation of migration effects on a Bayesian disease model||20||8:20 AM|
|Presenter||Caglar Koylu*, University of Iowa, Diansheng Guo, University of South Carolina, Analysis of Big Longitudinal Patient Mobility Data for Evaluating Efficiency of a Health Care System||20||8:40 AM|
|Presenter||Imam Xierali*, AAMC, Physician Multi-site Practicing in Georgia||20||9:00 AM|
|Discussant||Xun Shi Dartmouth College||20||9:20 AM|
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